WO2019175663A1

WO2019175663A1 - Method for generating a contact lens recommendation

Info

Publication number: WO2019175663A1
Application number: PCT/IB2019/000240
Authority: WO
Inventors: Mouad Lamrani; Stephen D. Newman
Original assignee: Menicon Co. Ltd.
Priority date: 2018-03-14
Filing date: 2019-03-13
Publication date: 2019-09-19
Also published as: WO2019175663A9

Abstract

Generating a contact lens recommendation can include analyzing a characteristic of at least one biomarker from a contact lens and comparing the characteristic with a database that correlates the characteristic with a contact lens recommendation.

Description

TITLE

Method for Generating a Contact Lens Recommendation

BACKGROUND

[0001] When a user wears a contact lens, proteins, lipids, antibodies, and other types of biological materials from the user’s tear and other optical fluid can be bonded to, adsorbed by, or otherwise deposited onto a surface of the user’s contact lens. In some examples, the bonding of proteins is a result of the protein denaturing, but in other situations, the protein has not denatured before adsorbing to the contact lens. Protein deposits that are visible to the naked eye are most often a result of denaturation. These proteins can build up on the surface of the contact lens, forming protein deposits that impact the transparency of the lens and the integrity of the lens surface. In some examples, the protein deposits trigger an immune reaction and the body produces antibodies in response. These antibodies can cause inflammation, irritation, redness, and itching in the eye.

[0002] The build-up of certain biological material can be indicative of a health condition of the contact lens wearer. Contact lenses have been modified to collect biological material within tear fluid or otherwise bind biological material to the surface of the contact lens to assess a health condition of the wearer. One or more health conditions might be reduced or alleviated, or increased comfort could be achieved, if the user were to wear contact lenses most compatible with their biological systems.

[0003] Traditional approaches for assessing patient health via tear fluid discuss specifically and structurally modifying a contact lens to collect information about the

composition of the user’s tears. U.S. Patent Publication No. 2014/0088381 issued to James Etzkom, et al. teaches an apparatus, systems and methods that employ contact lenses to facilitate testing for an analyte present within tear fluid. According to Etzkom, a contact lens can include a substrate that forms at least part of a body of the contact lens, and one or more cavities disposed within the substrate is configured to collect and store tear fluid over time when the contact lens is worn over an eye. Etzkorn also discloses a contact lens that includes a substrate that forms at least part of a body of the contact lens and one or more receptors disposed on or within the substrate, the one or more receptors being configured to bind to a known ligand. [0004] In another reference, U.S. Patent Publication No. 2004/0181172 issued to

Fiona Patricia Carney, et al., a contact lens is disclosed which can be used to collect one or more analytes of interest in a tear fluid, and in turn, determine the physiological state or health of an individual. Further, this reference teaches that a contact lens for collecting an analyte can be modified to have surface charges present in a density sufficient to impart to the contact lens an increased adsorption of the analyte of interest, a coating including a receptor which specifically binds the analyte of interest, molecular imprints for the analyte of interest, and a core material that is prepared from a composition containing a receptor which binds specifically the analyte of interest.

[0005] Further, U.S. Patent Publication No. 7,429,465 issued to Achim Muller, et al. teaches a process for analyzing an analyte in a hydrogel contact lens following its wear on the eye. The method includes physically or chemically inducing a volume reduction of the hydrogel contact lens and thereby squeezing the analyte out of the polymer material making up the contact lens and feeding the analyte obtained according to step (a) into an analyzer.

[0006] U.S. Patent No. 6,060,256 issued to Dennis S. Everhart, et al. teaches an inexpensive and sensitive device and method for detecting and quantifying analytes present in a medium. The device includes a metalized film upon which is printed a specific, predetermined pattern of analyte-specific receptors. Upon attachment of a target analyte to select areas of the plastic film upon which the receptor is printed, diffraction of transmitted and/or reflected light occurs via the physical dimensions and defined, precise placement of the analyte. A diffraction image is produced which can be seen with the eye or, optionally, with a sensing device.

[0007] U.S. Patent Publication No. 2001/0034500 issued to Wayne Front March, et al. teaches an ophthalmic lens including a receptor moiety that can be used to determine the amount of an analyte in an ocular fluid. The receptor moiety can bind either a specific analyte or a detectably labeled competitor moiety. The amount of detectably labeled competitor moiety which is displaced from the receptor moiety by the analyte is measured and provides a means of determining analyte concentration in an ocular fluid, such as tears, aqueous humor, or interstitial fluid. The concentration of the analyte in the ocular fluid, in turn, indicates the concentration of the analyte in a fluid or tissue sample of the body, such as blood or intracellular fluid. Each of these references is incorporated by reference for all that they contain. [0008] Despite the teachings of the aforementioned references, it would be desirable to provide a method for generating a contact lens recommendation using biomarkers that does not inconvenience the user by requiring the user to purchase and wear unconventional contact lenses, consult an ophthalmologist, or alter the user’s daily routine.

SUMMARY

[0009] In one aspect of the present disclosure, a method of generating a contact lens recommendation can include analyzing an aqueous solution using a measuring device to determine a characteristic of at least one biomarker within the aqueous solution. The aqueous solution can be positioned within a container which has been configured to house at least one contact lens. The method can also include receiving data relative to the biomarker characteristic from a database. The method can further include comparing the data with a plurality of biomarker characteristics stored within the database. The comparison between the data and the plurality of biomarker characteristics stored within the database can be accomplished using a computing device and/or a processor. The method can also include generating a contact lens recommendation based, at least in part, on the comparison.

[0010] Analyzing the aqueous solution using the measuring device can include emitting light through the aqueous solution and conducting a spectral analysis. The at least one biomarker within the aqueous solution can include a protein build-up on the contact lens. In some embodiments, the method can also include predicting a health condition of the user based on the comparison. The measuring device can include a sensor incorporated into a container holding the aqueous solution. The measuring device can include a sensor incorporated into a mobile device. In some embodiments, comparing the data with the plurality of biomarker characteristics stored within the database includes sending the data to a remote device, a mobile device, a networked device, or a combination thereof. In one embodiment, the at least one biomarker can be deposited into the aqueous solution by submerging the at least one contact lens within the aqueous solution.

[0011] In another aspect of the present disclosure, a method of generating a contact lens recommendation can include providing an aqueous solution configured to receive a contact lens from a user. The method can also include emitting light through the aqueous solution using a light source, and measuring at least one characteristic of the light source with a sensor. The method can further include sending data related to the at least one characteristic to a database and comparing the data to the contents of the database to generate a contact lens recommendation.

[0012] In one embodiment, the light source can emit isolated predetermined wavelengths of light through the aqueous solution. In other embodiments, the light source can emit a broad spectrum of wavelengths and the sensor can include at least one filter. The measuring step can include utilizing Raman spectroscopy. The database can be configured to organize and manipulate the data after the data has been received by the database. The method can also include the step of storing the data within the database. The method can further include the step of comparing the data to the contents of the database to determine a health condition of the user.

[0013] In yet another aspect of the present disclosure, a method of generating a contact lens recommendation can include providing an aqueous solution configured to receive a contact lens from the user. The method can also include analyzing the aqueous solution using a measuring device after a first duration of time to determine a first characteristic of a first biomarker within the aqueous solution. The method can further include analyzing the aqueous solution using the measuring device after a second duration of time to determine a second characteristic of a second biomarker within the aqueous solution. The method can also include the step of determining a change between the first and second characteristics and comparing the change with a database that correlates the first and second characteristics with recommended contact lenses. The method can further include generating a contact lens recommendation based on the comparison.

[0014] The step of analyzing the aqueous solution can include emitting light through the solution and measuring a light characteristic of the light using Raman spectroscopy. The change between the first and second characteristics can be a change in concentration of the first biomarker within the aqueous solution, or a rate of concentration change of the first biomarker within the aqueous solution. The first duration of time and the second duration of time can be equal in duration. The method can further include the step of replacing the aqueous solution with uncontaminated aqueous solution between the first duration of time and the second duration of time. [0015] In another aspect of the present disclosure, a computing device can include a processor and a memory. The processor can obtain information which indicates a characteristic of at least one biomarker which is derived from a contact lens used by a user. The processor can also generate a recommendation for a contact lens for the user based on the information.

[0016] The recommendation can include a contact lens material type. The contact lens material type can include at least one of: a hydrogel material, a silicone material, a silicone hydrogel material, a rigid lens material, a soft contact lens material, a daily disposable contact lens material, an extended wear contact lens material, and a rigid gas permeable contact lens material. The characteristic can be correlated with a health condition of the user. The processor can generate the recommendation based on the health condition. The health condition can include at least one of an eye condition, an eye comfort level, a dry eye level, an allergic condition, and/or an infection.

[0017] The biomarker can include at least one of a protein, an antibody, an electrolyte level, a sodium level, a chloride level, a potassium level, a calcium level, an iron level, a lysozyme level, a lactoferrin level, a lipocalin level, an albumin level, a cytokine level, an enzyme level, a lipid level, a proteases level, an osmolarity, a matrix metalloproteinase-9 level, an immunoglobulin E level, an immunoglobulin G level, an immunoglobulin A level, and an immunoglobulin M level. The processor can also obtain information which indicates a characteristic of at least one biomarker which is derived from a contact lens used by the user.

The processor can also be configured to obtain information which indicates a relative

characteristic of the biomarker which is derived from another contact lens used by the user. The processor can also generate a recommendation for a contact lens for the user based on the obtained information.

[0018] In some embodiments, the processor can also obtain information which indicates a characteristic of at least one biomarker which is derived from a contact lens worn by the user for a time period. The processor can also be configured to obtain information which indicates a characteristic of the biomarker which is derived from contact lens worn by the user for another time period. The processor can also generate a recommendation for a contact lens for the user based on the obtained information.

[0019] In another embodiment, the processor can also obtain information which indicates a characteristic of at least one biomarker which is derived from a contact lens worn on a first eye of the user. The processor can also be configured to obtain information which indicates a characteristic of the biomarker which is derived from a contact lens worn on a second eye of the user. The processor can also generate a recommendation for a contact lens for the user based on the obtained information.

[0020] In yet another aspect of the present disclosure, a non-transitory computer readable recording medium can store a program which causes the computer to execute the steps of obtaining information which indicates a characteristic of at least one biomarker which is derived from a contact lens used by a user and generating a recommendation for a contact lens for the user based, at least in part, on the information.

BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings illustrate various embodiments of the present apparatus and are a part of the specification. The illustrated embodiments are merely examples of the present apparatus and do not limit the scope thereof.

[0022] FIG. l is a cross-sectional view of an example of contact lens positioned on an eye in accordance with the present disclosure.

[0023] FIG. 2 is a cross-sectional view of an example of biomarkers adhered to a contact lens in accordance with the present disclosure.

[0024] FIG. 3 is a cross-sectional view of an example contact lens in a solution for analysis purposes in accordance with the present disclosure.

[0025] FIG. 4A illustrates a cross-sectional view of running a test on the solution containing biomarkers from a contact lens, according to one embodiment.

[0026] FIG. 4B illustrates a cross-sectional view of running a test on the solution containing biomarkers from a contact lens, according to another embodiment.

[0027] FIG. 5 is a block diagram of an example of a recommendation system in accordance with the present disclosure.

[0028] FIG. 6 is a block diagram of an example of a database in accordance with the present disclosure.

[0029] FIG. 7 is a cross-sectional view of an example of a recommendation system in accordance with the present disclosure. [0030] FIG. 8 is a block diagram of an example method for recommending a contact lens in accordance with the present disclosure.

[0031] FIG. 9 is a block diagram of another example method for recommending a contact lens in accordance with the present disclosure.

[0032] FIG. 10 is a block diagram of yet another example method for

recommending a contact lens in accordance with the present disclosure.

[0033] FIG. 11 is a block diagram of another example method for recommending a contact lens in accordance with the present disclosure.

[0034] FIG. 12 is an example mold for making a contact lens in accordance with the present disclosure.

[0035] FIG. 13 is yet another example mold for making a contact lens in accordance with the present disclosure.

[0036] FIG. 14 is an example of a mold for making a contact lens in accordance with the present disclosure.

[0037] FIG. 15 is an example of a spinning structure for making a contact lens in accordance with the present disclosure.

[0038] FIG. 16 is a block diagram of an example method for recommending a contact lens in accordance with the present disclosure.

[0039] FIG. 17A depicts a graphical representation of measured ocular surface temperature in accordance with the present disclosure.

[0040] FIG. 17B depicts another graphical representation of measured ocular surface temperature in accordance with the present disclosure.

[0041] Throughout the drawings, identical reference numbers designate similar, but not necessarily identical, elements.

DETAILED DESCRIPTION

[0042] A healthy human eye is coated with tear fluid. Generally, the tear fluid includes a base mucous layer that coats the cornea of the eye, an aqueous layer, and a lipid layer that protects the aqueous layer by forming an outer hydrophobic barrier that helps to retain the aqueous layer against the mucous layer. The aqueous layer includes metabolites, proteins, electrolytes, and other constituents. The make-up of the tear fluid can result, in part, from a physiological response to an illness or an allergy. In some examples, the make-up of the tear fluid can represent the physiological expression of an individual’s unique DNA.

[0043] The principles presented herein include a method of using the constituents of the tear fluid as biomarkers that can be analyzed to detect a user’s reaction to any number of contact lenses, and then using the collected data to recommend a contact lens for the user. These biomarkers can be collected on a contact lens worn by the user. Any appropriate type of contact lens can be used to collect the biomarkers. However, unaltered commercially available contact lenses from a wide variety of manufacturers for corrective vision are envisioned to be the contact lens that are used to collect the biomarkers. Biomarkers, such as proteins, generally start to bind to the contact lens as soon as the contact lens is placed over the user’s eye. Without modifying the contact lens as they are provided by the manufacturers, proteins, electrolytes, and/or other biomarkers in the tear fluid can bind to the contact lens. The number or concentration of proteins adsorbed or otherwise bound to the contact lens can be correlated to the contact lens material and a patient’s ocular health status. By collecting, organizing, and referencing biomarker

characteristics, and coordinating the collected biomarkers to the contact lens being worn during collection, a contact lens recommendation can be generated which correlates the biomarker characteristic ( e.g protein concentration, inflammation indicators) with a patient’s ocular health database and contact lens characteristics, and proposes a preferential contact lens type for future wear.

[0044] Generally, a user removes their contact lenses after wearing them for a period of time. Often, before the user retires to bed, the user removes their contact lens and places the contact lens in a storage case for the night. The storage case can include a storage solution that disinfects the contact lens and also breaks down the build-up on the contact lens. The storage solution can be an aqueous solution that causes the build-up on the contact lens to dissolve into the solution. After a period of time, the storage solution can be replaced with fresh storage solution to reduce the concentration of tear fluid constituents or other contaminants within the solution.

[0045] The storage solution can be analyzed to determine the type and/or concentration of biomarkers that dissolved into the solution from the contact lens. In some examples, the solution can be analyzed with the contact lens in the solution. In other examples, the contact lens can be removed from the solution before analyzing the biomarkers. [0046] In some embodiments, a sensor or a sensing device can be used to collect analyte information from the solution. Any appropriate type of sensor can be used to identify the type and/or concentration of the biomarkers within the solution. In some instances, the sensor can be incorporated into the contact lenses’ storage container. For example, an optical spectral analyzer can detect or otherwise measure light properties from a light source within the storage container. The spectral analyzer can measure the amount the light’s optical transmittance through the storage solution. In some examples, the light source passes light through the storage solution at isolated predetermined wavelengths and the spectral analyzer measures the optical

transmittance at each of the predetermined wavelength ranges. Each of the recorded

transmittances can correlate to the presence of specific kinds of biomarkers and their

concentrations. In one embodiment, the storage container can include the sensor, a processor, and a memory. The sensor can be configured to obtain information which indicates a

characteristic of at least one biomarker derived from a contact lens used by a user and stored in the storage container. The processor can be configured to send the information, including the detected biomarker and the contact lens type to a computing device, which generates a contact lens recommendation for the user based on the information.

[0047] In other examples, the sensor can be incorporated into a hand-held device.

In one case, the sensor can be incorporated into the user’s mobile device, such as a smart phone and/or electric tablet. In one of these examples, the user can direct a beam of light into the storage solution and measure a reflection.

[0048] In some embodiments, the measured values can be augmented with complementary information, such as an amount of time that the user wore the contact lens. For example, the user can interact with a user interface (technically the sensing device including the sensor) to input how long the user wore the contact lenses. In some examples, the user can be prompted to input the number of hours that the user wore the contact lens. In other examples, the user can be prompted to input the number of days that he or she wore the contact lenses, whether the user removed the contact lenses during the night, the time of when the storage solution was last replaced, other factors that can affect the concentration of biomarkers in the storage solution, or combinations thereof.

[0049] In some embodiments, the sensor (technically the sensing device including the sensor) or other sensing device can record measured values or data to determine a concentration of each of the desired biomarkers. The recorded measurements (i.e., the measured values) can be a numerical and categorical value which fall within a predetermined range of numerical values correlated with particular biomarkers. In some examples, the sensor

(technically a sensing device including the sensor) or a sensing device can record solution data in real time. Further, the sensor or sensing device can include local and/or cloud based logic to determine the type concentration, and/or other characteristics of the varying kinds of biomarkers. In some examples, the sensor or a sensing device can use learning algorithms, predictive models, data correlation models, clustering models, artificial intelligence, any other appropriate computational techniques, and combinations thereof. In some examples, the algorithms applied to data collected from the sensor or sensing device can include support vector machines, neural networks, decision trees, Gaussian mixture models, hidden Markov methods, and wavelet analysis. The models used to learn from data can include but are not limited to anomaly detection models, clustering models, classification models, regressions models or summarization models.

In some examples, the sensor or sensing device can include a database that stores data used to correlate or compare the identification/concentration of the biomarkers and a contact lens recommendation for the user.

[0050] In another embodiment, a sensing device can be used to detect a user’s ocular surface parameters related to corneal tribological properties. Such corneal tribological properties can be measured, analyzed, and recorded in the database. For example, a temperature profile of the user’s eye can be collected. Such tribological properties can identify the effect a particular contact lens can have on the ocular surface of the wearer’s eye. Such tribological properties can include reported patient characteristics, a response to ocular surface stimulation, a functional visual acuity, blinking parameters, tear biomarkers, a contact lens deposition analysis, ocular surface temperature, and ocular surface resistance to movement.

[0051] In some embodiments, a temperature of the ocular surface of a user’s eye can be measured over a period of time. For example, FIG. 17A depicts ocular surface

temperature measurements over a period of time. Three sets of measurements were collected from a contact lens (CL) wearer and the measurements were collected from the contact lens wearer in the morning, mid-day, and afternoon (i.e., CL-morning, CL-mid-day, and CL- afternoon). Temperature spikes within the data can represent the contact lens wearer blinking. The measurement data depicted in FIG. 17A illustrates that the ocular surface temperature of a contact lens wearer’s eye can vary over a given period of time. FIG. 17B also depicts ocular surface temperature measurements collected over a period of time. Two sets of ocular surface temperature measurements were collected in FIG. 17B. First, ocular surface temperature measurements were collected without a contact lens (CL) positioned on the user’s eye (i.e., Day l-No CL). Second, ocular surface temperature measurements were collected with a contact lens positioned on the user’s eye (i.e., Day l-CL 9h30). As illustrated in FIG. 17B, the ocular surface temperature of an eye can vary based on whether the user is wearing a contact lens. Such tribological properties can be measured and recorded within a database.

[0052] The measurements can be sent to a computing device that processes the data and/or other information collected by the sensor. In some examples, at least some computations are performed by the sensor or a sensing device before sending data to a computing device where the computations are completed. In other examples, the sensor sends raw data to the computing device. In this example, all data processing, including data cleaning, data management, data mining, and any application specific issues, can be performed remotely, away from the sensor. In some examples, information processing can include data preprocessing, for example in order to format or modify the data for use in subsequent processing. In some examples, data preprocessing can include formatting for matrix computations, data

normalization, data synchronization, and data filtering.

[0053] The determinations of the type of biomarkers, the characteristics of biomarkers, such as the concentration of the biomarkers, chemometric data such as ratio kinetics, peak, plateau, time constant, decay, and so forth, lens type, wear time, patient ocular health history, patient medical health history, and any other relevant factors can be compared to data points stored in a database. The database can be local to the computing device or the computing device can have remote access to the database. The data in the database can correlate the measured biomarker characteristics ( e.g different types and concentrations of biomarkers) with contact lens recommendations or health conditions, such as eye health conditions, allergic conditions, other physiological conditions, or combinations thereof. In some examples, the data in the database can be used as input or training data to implement supervised machine learning techniques, or other statistical learning approaches to solve prediction inference, or other data mining problems related to health conditions, such as eye health conditions, allergic conditions, other physiological conditions, or combinations thereof. [0054] These health conditions can correlate to certain contact lens types that are preferred by or beneficial to users. For example, a first type of contact lens can cause those with certain types of allergies to have discomfort. The allergy type can be detected in the database, and more comfortable types of contact lens can be recommended to the user. In some examples, the database directly correlates the biomarker characteristics directly to recommendations for types of contact lens. The recommendation can include the preferred types of contact lenses from users with similar biomarker characteristics. In some examples, the database is populated with user’s preferences or user provided grades for a contact lens based on comfort, dry eyes, or other considerations. The database can sort these preferences based on the user’s biomarker characteristics and direct input.

[0055] The database can also store information such as an amount or percentage of correlation between the user’s biomarker characteristics and their contact lens preferences. For example, if ninety -five percent of the users with a specific biomarker profile prefer the same type of contact lens, then the correlation rating can be considered high or strong and information regarding this correlation can be stored in the database. In other examples, if just fifty-five percent of the users with a specific biomarker profile have a preferred contact lens type, then the correlation rating can be considered lower, but still high enough to make a recommendation. Correlations with multiple biomarkers can be stored and considered in generating a contact lens recommendation. In those examples, where users with a certain biomarker profile have a plurality of preferred contact lenses, the recommendation can include each of the preferred contact lens, for example in a ranked list. In this situation, the computing device, with reference to the database, can determine which types of contact lenses are not preferred and warn the user against the use of those types of contact lenses. In some examples, the reasons why the contact lenses are preferred or are not recommended can be collected and stored within the database as preference information. This preference information can be shared with other users who have similar biomarker profiles.

[0056] In some examples, the database can be in communication with multiple users and data sources. As data relating to a user’s biomarker characteristics is collected, this data and data from a plurality of other users can contribute to the information stored within the database. In some examples, data collection can automatically launch a data management system of the database. In some examples, the data management system or another process can incorporate additional data into the database, such as health conditions of each of the users. As a result, the correlations in the database can include reports from the users. The computing device can update the database based on the reports from the users. In some examples, patient data can be used as predictors in a statistical machine learning process. In some examples where the database is built using thousands of users, the database’s input can identify correlations between contact lens preferences and specific levels of different types of biomarkers that are unknown to the scientific community. Thus, even before scientific studies can be conducted to find a correlation between a biomarker and a health condition or contact lens recommendation, the computing device can, with reference to the database, send information related to the contact lens recommendation based on mathematically detected correlations. In some examples, if the user does not have a contact lens preference, no preferences have to be sent. In some situations, those contact lenses that the user does not like can also be sent to the database. As a result, the correlations in the database can also be derived from user reports. In some examples where the database is derived using information from thousands of users, the database’s input can identify correlations between user preferences and biomarker profiles.

[0057] These principles can allow a vast database to be built that correlates the contact lens preferences of the users with varying parameters of the biomarkers (ie., biomarker characteristics). For example, the database can include supplementary user data such as age, gender, weight, height, health history, and the like.

[0058] These principles also allow the user to have a non-invasive procedure to measure the biomarkers and receive a contact lens recommendation. Further, in those examples in which the user is already storing and cleaning his or her contact lens from time to time, the user can incur little to no additional effort in measuring the biomarkers and receive reports on a contact lens recommendation.

[0059] The recommendation can include recommending a certain lens material.

For example, certain lens materials can react with a user’s eye to cause inflammation or make the user’s eye prone to infection. In some examples, the contact lens can have a wrong prescription that can cause the eye to react by producing a certain biomarker. In this case, the

recommendation can include having the eye prescription checked. In yet other examples, the recommendation can include switching to a different contact lens type, such as daily disposable lens, rigid gas permeable lens, soft contact lens, and so forth. In some examples, the recommendation can include specific brands of contact lenses.

[0060] Referring now to the figures, FIG. 1 depicts an example of a contact lens

110 situated on the outside of a human eye 150. The contact lens 110 spans a portion of the outside surface of the exposed portion of the eye 150. An upper portion of the contact lens 110 is adjacent a set of eyelashes 152 of the upper eye lid. The contact lens 110 can include a posterior side that is in contact with the cornea of the eye 150, and an anterior side that is opposite of the posterior side. As the eye lid travels over the eye 150, the eye lid can move across the anterior side of the contact lens 110.

[0061] A user can wear the contact lens for vision correction purposes. In this type of example, the contact lens can include an optic zone 120 and a peripheral zone 122. The optic zone 120 can include a region that focuses light to the center of the user’s retina 124. The peripheral zone 122 can contact the eye near or over the sclera. While this example discloses using commercially available contact lenses configured for vision correction to be worn on the eye, other types of contact lenses can be used in accordance with the principles described in the present disclosure. For example, the contact lens may not include a curvature or other features configured to correct vision. Indeed, a physician can prescribe contact lenses for the sole purpose of collecting biomarkers within the patient’s tear fluid, in one embodiment.

[0062] The contact lens 110 can be a soft contact lens, rigid gas permeable

(RGP) contact lens, orthokeratology contact lens, another type of contact lens, or combinations thereof. The contact lens can be made of any appropriate type of material. A non-exhaustive list of materials that can be used to construct the contact lens can include any appropriate silicone material and/or hydrogel material. Such material can be formed of polymers, such as tefilcon, tetrafilcon A, crofilcon, helfilcon A&B, mafilcon, polymacon, hioxifilcon B, lotrafilcon A, lotrafilcon B, galyfilcon A, senofilcon A, sifilcon A, comfilcon A, enfilcon A, lidofilcon B, surfilcon A, lidofilcon A, alfafilcon A, omafilcon A, vasurfilcon A, hioxifilcon A, hioxifilcon D, nelfilcon A, hilafilcon A, acofilcon A, bufilcon A, deltafilcon A, phemfilcon A, bufilcon A, perfilcon, etafilcon A, focofilcon A, ocufilcon B, ocufilcon C, ocufilcon D ocufilcon E, ocufilcon F, phemfilcon A, methafilcon A, methafilcon B, vilfilcon A, other types of polymers, monomers, or combinations thereof. These materials can include various combinations of monomers, polymers, and other materials to form the material that makes up the contact lens. [0063] In one embodiment, the contact lens material can be made of hydrogel polymers without any silicone. This can be desirable to increase the wettability of the contact lens. In another embodiment, the contact lens material can be made of silicone hydrogel material.

[0064] The tear fluid in the ocular cavity can come into contact with the contact lens. In some examples, the entire surface area of the contact lens can come into contact with the tear fluid. The constituents of the tear fluid can include lipids, electrolytes, metabolites, proteins, antibodies, other types of compounds, or combinations thereof. These constituents can be biomarkers that can be indicative of a health condition, a genetic condition, an eye condition, another type of condition, or combinations thereof of the user. These biomarkers can bind to the contact lens.

[0065] A non-exhaustive list of biomarkers from the tear fluid that can be of interest includes, but is not limited to, electrolytes, sodium, potassium, chloride, phenylalanine, uric acid, galactose, glucose, cysteine, homocysteine, calcium, ethanol, acetylcholine and acetylcholine analogs, ornithine, blood urea nitrogen, creatinine, metallic elements, iron, copper, magnesium, polypeptide hormones, thyroid stimulating hormone, growth hormone, insulin, luteinizing hormones, chorionogonadotrophic hormone, obesity hormones, leptin, serotonin, medications, dilantin, phenobarbital, propranolol, cocaine, heroin, ketamine, hormones, thyroid hormones, ACTH, estrogen, cortisol, progesterone, histamine, IgE, cytokines, lipids, cholesterol, apolipo protein Ai, proteins and enzymes, lactoferrin, lysozyme, tear-specific prealbumin or lipocalin, albumin, complement, coagulation factors, liver function enzymes, heart damage enzymes, ferritin, virus components, immunoglobulins such as IgM, IgG, proteases, protease inhibitors, lactate, ketone bodies, other types of biomarkers, or combinations thereof.

[0066] In some embodiments, commercially available contact lenses can have surface properties that allow the biomarkers to bind to the contact lens without any modifications to the contact lens. Conventionally, protein build-ups and other types of build-ups on the surface of a contact lens are considered a problem on a regular contact lens that does not have surface modifications to enhance a biomarker’s ability to bind to the contact lens. In other examples, the contact lens can be modified to enhance the binding ability of particular biomarkers or biomarkers in general. In those embodiments in which the surface of the contact lens can be modified to enhance an ability to bind to the biomarkers, the binding enhancements can be made to any appropriate location on the contact lens, including, but not limited to, the peripheral zone, the optical zone, the anterior side of the contact lens, the posterior side of the contact lens, other areas of the contact lens, or combinations thereof. In one example where the contact lens is modified to enhance its ability to collect biomarkers, micro-cavities can be formed in the contact lens material that are shaped and sized to encourage an intake of tear fluid through capillary action.

[0067] FIG. 2 depicts an example of biomarkers 114 attached to the posterior surface 130 of the contact lens. While this example depicts the biomarkers 114 attached to the posterior surface 130 of the contact lens, the biomarkers 114 can be attached to only the anterior surface 132 or to both the anterior surface 132 and posterior surface 130 of the contact lens 110. In some examples, the biomarkers 114 can be adsorbed, absorbed, bonded, covalently bonded, ionically bonded, adhered, cohered, or otherwise connected to a surface of the contact lens 110.

In some examples, the biomarkers 114 are incorporated into the thickness of the contact lens 110

[0068] When the contact lens 110 is removed from the user’s eye, the biomarkers

114 can stay with the contact lens 110 as depicted in FIG. 2. The amount of biomarkers 114 that are attached to the contact lens 110 can be related to the amount of time that the contact lens 110 was on the eye. In some examples, the contact lens 110 can be worn by the user during that day and removed at night. Under these circumstances, biomarkers 114 can cover a substantial amount of the contact lens’ surface area. However, in other examples, the contact lens 110 can be worn by the user for a smaller period of time. In one specific instance, a patient can be provided with a contact lens 110 for a period of minutes in a doctor’s office to collect biomarkers 114 for analysis. In other examples, a patient can be instructed to keep a contact lens 110 in for a matter of hours or some other duration of time to collect the desired amount of biomarkers 114.

[0069] FIG. 3 depicts an example of a contact lens 110 in a storage container 140 with an internal cavity 102. The cavity 102 can be defined by a first wall 104 and a second wall 106 which are connected together bottom surface 108. A contact lens 110 and a solution 112 can also be disposed within the cavity 102.

[0070] The solution 112 can include a cleansing agent, such as a hydrogen peroxide or another type of agent to clean the contact lens and kill bacteria, fungus, other types of germs, or combinations thereof. The solution 112 can be an off-the-shelf type of storage solution that hydrates and cleans the contact lens. The storage solution 112 can cause the biomarkers 114 to dissolve into the solution 112 thereby cleaning the contact lens 110. The contact lens 110 can remain in the storage solution 112 until the contact lens 110 is later retrieved by the user. In some examples, the contact lens 110 is immersed into the solution for a short period of time, such as a few minutes. In other examples, the contact lens 110 can remain in the solution for multiple hours, such as overnight. With the biomarkers 114 removed from the contact lens 110, the biomarkers 114 can be diluted into the solution 112 where the biomarker types, their respective concentrations, or other biomarker characteristics can be measured or analyzed.

[0071] The biomarkers 114 can be removed from the contact lens 110 without adversely affecting the contact lens 110. In those examples, the contact lens 110 can be re-worn by the user. In some examples, the contact lens 110 is removed from the solution 112 so that the contact lens 110 is not affected by the testing mechanism performed on the solution 112. In other examples, the contact lens 110 can remain in the solution 112 while the solution 112 is being measured or analyzed, but the analysis does not adversely affect the contact lens 110, so that the contact lens 110 can be re-worn by the user.

[0072] In some examples, the biomarkers 114 can be analyzed in the storage container 140. In other examples, the solution 112 can be transferred to another type of device with a sensor for taking the measurements. In yet another example, a hand-held device can incorporate a sensor configured to perform the measurements or analysis on the solution 112.

[0073] One approach of analyzing the solution is depicted in FIG. 4A. In some embodiments, an optical spectral analyzer can be incorporated into the storage solution container 140. In the example depicted in FIG. 4A, a storage container 140 for a contact lens 110 includes a cavity 102 that is defined by at least one wall 104 that is connected by a floor 126. In some examples, a single circular wall can define at least a portion of the cavity 102. In other examples, multiple independent walls are joined together to define the cavity 102.

[0074] A light source 142 can be incorporated into a first side of the cavity 102.

The light source 142 can be oriented to direct a beam of light 144 through the solution 112 to a light receiver 146. As the beam of light 144 is transmitted through the solution 113, a portion of the light can be absorbed by the solution depending on its contents. A solution 112 with a different type of biomarker 114 can cause a different or unique light transmittance through the solution 112. Further, a solution 112 with a different concentration of the same biomarker 114 can also exhibit a different or unique light transmittance.

[0075] In some embodiments, the light source 142 can be configured to transmit a range of isolated wavelengths independently through the solution 112. The transmittance for each wavelength can be measured. Certain biomarkers in the solution 112 may not affect the optical transmittance at a first wavelength, but can affect the optical transmittance at a second wavelength. Thus, by transmitting or otherwise emitting light at different wavelengths, a more refined measurement of the solution’s composition can be measured and recorded. The measured transmittances at each wavelength can be compared to other solutions wherein the types and concentrations of the biomarkers are known. Thus, the measured transmittance levels can be correlated to the types and concentration of the biomarkers 114 in the solution 112.

[0076] Other types of spectroscopic methods can be used to identify the types and concentration of the biomarkers in the solution. In some examples, measuring a frequency, rather than a wavelength, can be performed by the light receiver 146 ( e.g ., spectral analyzer). A non- exhaustive list of other types of spectroscopic mechanisms for analyzing the solution can include atomic absorption spectroscopy, attenuated total reflectance spectroscopy, electron paramagnetic spectroscopy, electron spectroscopy, Fourier transform spectroscopy, gamma-ray spectroscopy, infrared spectroscopy, laser spectroscopy, mass spectrometry multiplex or frequency-modulated spectroscopy, Raman spectroscopy, and x-ray spectroscopy. Additionally or alternatively, ultraviolet absorbance at 280 nm, turbidity, and light scattering can be used to analyze the solution for biomarker characteristics. Concerning ultraviolet absorption, the intensity of the ultraviolet absorbance can depend on the tryptophan and tyrosine content of the proteins. Such characteristics can be correlated in a database to a calibration curve with known concentration of proteins. The analysis can be aided or otherwise enhanced by incorporating a colorimetric assay into the solution (e.g., binding a dye to the biomarker or biomarkers).

[0077] While the example embodiment of FIG. 4 A includes the light source 142 and the light receiver 146 on different sides of the cavity walls, the light source 142 and the light receiver 146 can be on the same side of the cavity 102. In such an example, light emitted from the light source 142 can be reflected within container and the reflection can be recorded or otherwise measured by the light receiver 146 (e.g, a spectral analyzer). [0078] In some examples, the sensor can be part of a hand-held device 702 depicted in FIG. 7. In this example, the hand-held device includes a sensor, such as an infrared spectrometer, that can measure a concentration of a biomarker within the solution. For example, the hand-held device can include an end that has an infrared source that sends infrared light into the solution when the user orients the hand-held device to appropriately direct the infrared light and instructs the hand-held device to send the light. The amount of infrared light that is absorbed into the solution can be based, at least in part, on the constituents within the solution. Thus, the returning amount of the infrared light to the hand-held device can be measured using, for example, an infrared receiver incorporated into the hand-held device.

[0079] In other embodiments, a sensor or a sensing device within the storage solution container 140 can be configured to detect a pH level or pH value within the storage solution container 140, for example, through colorimetric paper-based assay. The pH level or pH value within the storage solution container 140 can indicate microbial contamination or other biomarker characteristics. In some embodiments, the pH level or pH value is measured without solution 112 in the storage solution container 140. In other embodiments, the pH level or pH value is measured with solution 112 in the storage solution container 140. The use of a colorimetric paper-based assay can produce a colorimetric output, based at least in part on ultraviolet absorbance.

[0080] In yet other examples, the solution 112 can be poured into another device for analysis. In one case, the solution 112 can be poured into an immunodiffusion machine, a centrifuge, another type of device, or combinations thereof for measuring at least one property (e.g, a biomarker characteristic) of the solution 112.

[0081] Another approach of analyzing the solution is depicted in FIG. 4B. In some embodiments, at least one electrode can be incorporated into the storage solution container 140 to analyze the contents of the storage solution 112 by chronoamperometry. In the example of FIG. 4B, an electrical potential can be applied to an electrode 148 over a predetermined time period to elicit a resultant current intensity. The current intensity can vary relative to the properties of the solution 112. For example, the current intensity measured at the electrode 148 can vary relative to the concentration of glucose within the solution 112, in one embodiment.

The current intensity of the electrode 148 can be recorded and compared with a database, either alone or along with other collected data, to determine a health condition of the contact lens user. [0082] The electrode 148 can be incorporated into the floor 126 of the container

140. In some embodiments, a stepped potential or voltage can be applied to the electrode 148 wherein the voltage applied to the electrode 148 increases by predetermined steps over a period of time. In other embodiments, the potential or voltage applied to the electrode 148 can be a constant potential over a period of time. A plurality of electrodes comprising an array of electrodes can be incorporated into the floor 126 or any other surface of the container 140. The electrode 148 can be operably coupled to a power supply (not shown) configured to supply electrical power to the electrode 148. The electrode 148 can be operably coupled to a processing unit (not shown) configured to measure operational parameters of the electrode ( e.g ., voltage, current, time, etc.).

[0083] FIG. 5 depicts a diagram of a contact lens recommendation system 500.

The system 500 includes a base station 505 having a processor 515, an input/output (I/O) controller 520, and memory 525. In some embodiments, the processor 515 and the memory 525 are components or subcomponents of a computing device, for example, the base station 505 can be a computing device. The I/O controller 520 can be in communication with a sensing device 530, for example, through an antenna. In some examples, a sensor of the sensing device 530 can be incorporated into the contact lens storage case, into a hand-held device, an independent machine configured to analyze the solution, another type of sensor, or combinations thereof. In some examples, the sensing device can include its own processor, memory, and/or I/O controller. The components of the system and the sensing device 530 can communicate wirelessly, through hard wired connections, or combinations thereof. The memory 525 of the system can include a biomarker characteristic obtainer 545, a database 550, a biomarker and database comparer 555, and a recommendation generator 560. In some embodiments, the system 500 can further include a base station 505 in communication with the memory 525, the base station 505 can be in communication with the processor 515 and/or the sensing device 530, for example via an antenna within the I/O controller 520 or a transponder. In some embodiments, the sensing device 530 is at least one electrode and/or optical spectral analyzer.

[0084] The processor 515 can include an intelligent hardware device, (e.g., a general-purpose processor, a digital signal processor (DSP), a central processing unit (CPU), a microcontroller, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof). In some embodiments, the processor 515 can be configured to operate a memory array using a memory controller. In other embodiments, a memory controller can be integrated into the processor 515. The processor 515 can be configured to execute computer-readable instructions stored in a memory 525 to perform various functions (e.g., functions or tasks supporting the evaluation of the prescribed optical devices).

[0085] The I/O controller 520 can include a modem, a keyboard, a mouse, a touchscreen, or a similar device. In some examples, the I/O controller 520 can be implemented as part of the processor 515. In some examples, a user can interact with the system via the I/O controller 520 or via hardware components controlled by the I/O controller 520. The I/O controller 520 can be in communication with any input and any output of the system 500.

[0086] The memory 525 can include random access memory (RAM) and read only memory (ROM). The memory 525 can store computer-readable, computer-executable software including instructions that, when executed, cause the processor to perform various functions described herein. In some examples, the memory 525 can include, among other elements, a basic input/output system (BIOS) which can control basic hardware and/or software operation such as the interaction with peripheral components or devices. The memory 525 storing the software (e.g., a program) can be referred to as a "computer readable recording medium." The recording medium can be a "non-transitory tangible medium" such as, for example, a tape, a disk, a card, a semiconductor memory, a programmable logic circuit, or the like. The program can be supplied to the computer via any transmission medium (such as a communication network or a broadcast wave) that can transmit the program. In some

embodiments, aspects of the present disclosure can also be achieved in the form of a computer data signal in which the various programs are embodied via electronic transmission and which is embedded in a carrier wave.

[0087] The biomarker characteristic obtainer 545 can include programmed instructions that cause the processor 515 to measure or record a biomarker characteristic from the solution. In other words, the processor 515 can execute the programmed instructions to function as the biomarker characteristic obtainer 545. The characteristic can include a biomarker identification, a biomarker concentration, another type of characteristic, or combinations thereof. In some examples, the biomarker characteristic obtainer 545 passively receives a signal containing information about the biomarker characteristic. In other examples, the biomarker characteristic obtainer 545 actively requests information about the biomarker characteristic.

[0088] The database 550 can include a data structure that holds information relating to the biomarker characteristics. The database 550 can include information relating to biomarker characteristics that have been recorded or measured in labs, for example, by chemometric methods, obtained from at least one user, or combinations thereof. In some examples, the database can be initially populated with information from users with a history of wearing contact lenses that know certain contact lens types are comfortable for them, caused them discomfort, or had a different experience. These users can submit their biomarker profiles (i.e., personal biomarker information) along with their contact lens history. In some examples, the users have their biomarker profiles analyzed or otherwise correlated with the database to detect a health condition or for another reason other than a contact lens recommendation. In some examples, thousands to millions of biomarker profiles can be collected in the database.

[0089] The biomarker and database comparer 555 can represent or otherwise include programmed instructions that cause the processor 515 to compare the obtained biomarker characteristic, along with any other additional contextual or health information related to the contact lens and/or the user, against the information stored in the database 550. In other words, the processor 515 can execute the programmed instructions to function as the biomarker and database comparer 555. In some examples, the programmed instructions can include data mining algorithms to compare biomarker characteristics. The recommendation generator 560 can represent or otherwise include programmed instructions that cause the processor 515 to generate a contact lens recommendation based, at least in part, on the user’s biomarker profile. In other words, the processor 515 can execute the programmed instructions to function as the

recommendation generator 560.

[0090] In some embodiments, correlations between certain biomarkers and their respective concentrations can be realized with a larger sample size of patient information than the correlations between certain biomarkers that might be realized using only the information provided by an individual patient or user. For example, an analysis can be run on all the biomarker characteristics of users with a specific contact lens preference. Such an analysis can reveal that certain biomarkers that had not previously been linked to that contact lens preference has a statistically significant normal concentration level, a statistically significant low concentration level, a statistically significant high concentration level, another statistically significant concentration level, a statistically insignificant type of concentration level, or combinations thereof that had not previously been observed.

[0091] In some embodiments, a recommendation can include a confirmation request to confirm whether or not the user has a good experience with a particular recommended contact lens. In the examples where a confirmation request is sent and a confirmation message is received, the results of the confirmation test can be sent to a computing device. The results can be used to assist the database 550 and its associated analytics to improve future

recommendations. The confirmation can be conducted by a device that is commonly used by the user ( e.g ., a mobile phone, laptop, etc.).

[0092] FIG. 6 depicts an example of a database 600 that associates or otherwise correlates a characteristic of the tear chemistry, eye condition (e.g., a health condition), and contact lens recommendation. In this example, the database 600 can include a first column 602 that includes the tear chemistry information (e.g, biomarker characteristics), a second column 604 that includes eye condition information, and a third column 606 that includes the contact lens recommendation. The database 600 can include a first row 608 that includes the correlation for a tear chemistry with a normal first biomarker level and a normal second biomarker level, a second row 610 that includes the correlation for a tear chemistry with a normal first biomarker level and a high second biomarker level, a third row 612 that includes the correlation for a tear chemistry with a low first biomarker level and a normal second biomarker level, a fourth row 614 that includes the correlation for a tear chemistry with a low first biomarker level, a fifth row 616 that includes the correlation for a tear chemistry with a high first biomarker level, and a sixth row 618 that includes the correlation for a tear chemistry with a high second biomarker level.

[0093] While the example of FIG. 6 depicts an embodiment with correlations of a first and second biomarker, any number of biomarker correlations can be included in the database. In some embodiments, characteristics correlated with a single biomarker can be included as depicted in rows 614, 616, 618. In other embodiments, the characteristics correlated with a specific set of biomarkers can be included. For example, recommendations correlated with two or more characteristics of different types of biomarkers can be included as depicted in rows 608, 610, 612. Any appropriate number of biomarker characteristics can be included. For example, three to hundreds of characteristics can be collectively correlated to a specific type of health condition. In the example shown in FIG. 6, whether a biomarker level is "Normal",

"Low", or "High" can be determined by comparing the measurement value of the biomarker with a predetermined threshold.

[0094] FIG. 7 depicts an embodiment of a system 700 for recommending a contact lens to a user. In one embodiment, a storage solution ( i.e ., aqueous solution) can be contained within a contact lens container 140. A hand-held device 702 with a sensor can be used to take a measurement of at least one characteristic of the biomarkers in the solution. The hand- held device 702 can, according to one embodiment, send the recorded levels to a mobile device 704 {i.e., a computing device) that is in communication with a cloud based data center 706 that stores the database (FIG. 6, 600). The mobile device 704 can relay the recorded levels to the database in the data center 706, which can send the correlations and contact lens

recommendations back to the mobile device 704. The mobile device 704 can present the results from the hand-held device 702 and/or the correlations from the database in a user-interface of the mobile device 704.

[0095] At least some of the processing of the measurement data obtained from the return signals from the storage solution can occur at the hand-held device 702, the mobile device 704, and/or the data center 706. In some examples, the mobile device 704 includes a program that retrieves the correlations from the database and performs additional tasks. For example, the mobile device 704 can retrieve information about the recommended contact lens from another source other than the database in response to receiving the recommendation from the database. The mobile device 704 can also, in response to receiving the contact lens recommendation, retrieve a health professional’s contact information that can provide that type of contact lens, consult a user’s calendar to set up an appointment with the health professional, schedule an appointment with the health professional, perform another task, purchase that type of contact lens, request samples of that type of contact lens for the user, or combinations thereof.

[0096] FIG. 8 illustrates an example method 800 for recommending a contact lens. In one embodiment, the method 800 can include analyzing 802 a characteristic of at least one biomarker contained on a contact lens and comparing 804 the characteristic with a database that correlates the characteristic with a contact lens recommendation.

[0097] At block 802, a characteristic of at least one biomarker is analyzed or otherwise measured. This process can be performed by the sensing device 530 or by the processor 515 ( e.g ., the biomarker characteristic obtainer 545) after the processor 515 obtains the measurements taken by the sensor of the sensing device 530. The biomarkers can be obtained from a contact lens. In some examples, the biomarkers remain on the contact lens when the biomarkers are being analyzed or otherwise measured. In other examples, the biomarkers can be removed from the contact lens before the analysis. The biomarker characteristic can include a type of biomarker, a concentration of biomarker, a location of the biomarker on the contact lens, another type of characteristic, or combinations thereof. The biomarker characteristic can involve a single biomarker. In other examples, the biomarker characteristic includes the collective condition of multiple biomarkers.

[0098] At block 804, the characteristic can be compared to a database (e.g., the database 550 referenced in FIG. 5) that correlates the characteristic with a contact lens type or recommendation. This process can be performed by the processor 515 (e.g, the biomarker and database comparer 555). For example, the database can include the type and concentration of a single biomarker that is correlated with a specific type of contact lens. In one embodiment, the database can correlate a first type of biomarker having a first concentration with a second type of biomarker having a second concentration to recommend a specific type of contact lens.

[0099] FIG. 9 illustrates an example method 900 for making a contact lens recommendation. In one embodiment, the method 900 can include obtaining 902 biomarkers from a contact lens previously worn by a user, analyzing 904 at least one biomarker to determine the eye condition of the user, and making 906 a contact lens recommendation based on the eye condition. The process block 904 can be performed by the same entity (e.g, a processor) as that of block 802 in FIG. 8. The process block 906 can be performed by the processor 515 (e.g, the recommendation generator 560).

[00100] At block 902, the biomarkers can be obtained from the contact lens in any appropriate way. In some examples, the biomarkers can dissociate from the contact lens in a multiple purpose contact lens storage solution. In another example, the biomarkers can be obtained from the contact lens by wiping a material across the contact lens’ surface. In yet other examples, the biomarkers can be removed from the contact lens by scratching the biomarkers off of the lens’s surface. In some examples, obtaining the biomarkers from the contact lens results in a contact lens that can be re-worn by the user. In other examples, obtaining the biomarkers from the contact lens results in modifying the contact lens such that it cannot be re-worn by the user. The biomarker characteristic obtainer 545 obtains from, for example, the sensing device 530, information indicating characteristics of the biomarkers obtained as above.

[00101] FIG. 10 illustrates an example method 1000 for making a contact lens recommendation. In one embodiment, the method 1000 can include comparing 1002 a characteristic of biomarkers from a contact lens previously worn by a user to an aggregated database that correlates characteristics of biomarkers, the contact lens worn, the user’s health history or conditions, with contact lens recommendations. The process block 1002 can be performed by the same entity as that for the block 804 in FIG. 8.

[00102] The aggregated database can include measurement data or information associated with contact lens recommendations from multiple sources. In one embodiment, doctors, patients, other types of professionals, other types of sources, or combinations thereof can contribute information to the database. In some embodiments, thousands or millions of health conditions and/or contact lens recommendations with their associated biomarker characteristics can be aggregated into the database.

[00103] Further, after the contact lens recommendation is sent to the user, the user can have an option to confirm whether the recommendation was accurate or otherwise helpful. For example, a user can place his or her contact lens in the storage case and receive a recommendation indicating that another contact lens can be a better fit for the user. As a result, the user can purchase that type of contact lens. In the event that the user likes the recommended contact lens, the user can send a confirmation message to the computing device to update the database to indicate the user’s experience with the contact lens. The confirmation message can increase a confidence level of the correlation between the characteristic of the biomarker and the recommendation. In the event that the user does not have a good experience with the

recommended contact lens after trying them, the user can send a confirmation message to the database indicating the poor experience. This confirmation message can cause a decrease in a confidence level of the correlation between the biomarker profile and the recommended contact lens. In the event that the user does not like the recommended contact lens, the database can reassess the correlation drawn and determine whether the correlation drawn is based on proper assumptions.

[00104] FIG. 11 illustrates an example method 1100 for recommending a contact lens. In one embodiment, the method 1100 includes dissolving 1102 a build-up of biomarkers on a contact lens into a solution, analyzing 1104 the constituents of the build-up in the solution, sending 1106 at least one parameter derived from the analysis to a computing device; and receiving 1108 a contact lens recommendation from the computing device. The process blocks 1104 and 1106 can be performed by, for example, the sensing device 530. The process block 1108 can be performed by, for example, a mobile device.

[00105] At block 1102, the biomarker build-up can be dissolved by placing the contact lens into a contact lens storage solution. Any appropriate type of contact lens solution can be used. For example, the contact lens solution can be a hydrogen peroxide solution, a multiple purpose storage solution, another type of solution, or combinations thereof.

[00106] In some examples, the contact lens solution includes hyaluronan, sulfobetaine, poloxamine, boric acid, sodium borate, ascorbic acid, edetate disodium, sodium chloride, hydroxyalkyl phosphate, poloxamer, sodium phosphate buffer, polyoxyethylene polyoxypropylene block copolymer with ethylene diamine, and polyaminopropyl biguanide, or combinations thereof. The contact lens can include a disinfectant, a surfactant, an anti-fungal agent, an anti -bacterial agent, another type of agent, or combinations thereof.

[00107] Removal of the biomarkers from the contact lens into the solution can occur over any appropriate time period. In some examples, the biomarkers are in the solution for at least one minute, at least five minutes, at least 20 minutes, at least 45 minutes, at least an hour, at least two hours, at least 5 hours, at least 7 hours, at least one day, at least two days, another appropriate time period, or combinations thereof.

[00108] In some examples, the contact lens is free of surface cavities that are constructed to be binding sites for biomarkers or to draw in tear fluid into the contact lens. In some examples, the contact lens is free of surface treatments that target the binding of specific biomarkers to the contact lens. In other embodiments, the contact lens can contain surface cavities or surface treatments intended to target the binding of biomarkers to the contact lens.

[00109] In some embodiments, the storage solutions includes binding agents that are configured to facilitate the bonding between a surface of the contact lens and a biomarker from the tear fluid. In other examples, no binding agents are introduced to the contact lens solution. The contact lens can include a surface in which the biomarkers are as likely to bind to any surface of the contact lens as any other surface of the contact lens. In some examples, the biomarkers can attach to the optical zone of the contact lens, a peripheral zone of the contact lens, an edge of the contact lens, a posterior side of the contact lens, an anterior side of the contact lens, another area of the contact lens, or combinations thereof.

[00110] The dissolved contents can then be analyzed at block 1104, for example according to the process 802 or 904 described herein with reference to FIGS. 8 and 9, respectively. At block 1106 at least one parameter derived from the analysis can be sent to a computing device, for example as described with reference to FIG. 7. At block 1108, the user (via a mobile device or other computing device) can receive a contact lens recommendation from the computing device. In some embodiments, the recommendation can be derived from the at least one parameter sent to the computing device, according to the methods described herein.

[00111] The contact lens can be made through any appropriate mechanism. In some embodiments, the contact lenses are molded into their shape. In other embodiments, the contact lenses are machined to their precise shape. In yet other embodiments, the contact lens are cast molded or spin-cast molded. Spin cast contact lenses can have an advantage of making a continuous surface on the posterior side of the contact lens that matches a profile constructed to assist the user with his or her vision. The front side of the contact lens during a spin casting procedure can include a profile that matches a contact lens mold. The contact lens mold can include a continuous, curved surface without interruptions. In some embodiments, the spin cast contact lenses provide for a continuous surface that is substantially free of interruptions, such as micro-cavities. In other embodiments, having a continuous, interruption free surface on both the anterior side and the posterior side can prevent the collection of tear fluid in the contact lens. Avoiding the collection of tear fluid can prevent the contact lens from having an additional amount of weight. Further, unnecessary tear fluid can combine with the solution to skew the chemistry of the solution and cause flawed recommendations. In some embodiments in which tear fluid is not collected, the biomarkers can be carried with the contact lens into the solution. Thus, the analysis may not have to be adjusted to accommodate an increase in fluid. In some examples, the amount of fluid being analyzed may not require a precise amount of fluid. In one example, the lens case can include a fill line and the measurements performed by the sensor can be sufficient if the solution is close to the fill line, but not required to be precisely at the fill line. Further, by not modifying the contact lens to have an enhanced ability to collect specific biomarkers, the concentrations of the biomarkers that bind to the contact lens can be more reflective of the actual concentration of that biomarker in the tear fluid. An enhanced ability to collect a particular biomarker or a wide variety of biomarkers can cause a disproportionate amount of that biomarker to bind to the contact lens, which can skew the measurement data when analyzing the solution and potentially lead to an inaccurate characterization of the biomarker’s actual concentration.

[00112] FIGS. 12-15 illustrate various components that can be used in certain examples for making a contact lens 110 in accordance with the principles described in the present disclosure. A liquid lens material 1052 can be applied to a profile 1054 of the mold 1042. The mold 1042 and the liquid lens material 1052 can be loaded into a spinning structure 68 that is configured to spin the mold 1042 so that the liquid lens material 1052 centrifugally spreads across the profile 1054 into the desired shape of the contact lens. A curing agent (e.g., temperature, actinic radiation, or another type of curing agent) can be exposed to the liquid lens material 1052 while the mold 1042 is spinning. As a result, the liquid lens material 1052 can harden into the contact lens 110.

[00113] FIG. 12 is a cross-sectional view of one embodiment of a mold for a contact lens according to the principles of the present disclosure. In one embodiment, the mold 1042 can have a base 1056 with multiple cut outs 1058, 1060, 1062, which can be spaced and shaped to interlock with an internal surface of a spinning structure during a later stage of manufacturing. The profile 1054 of the mold 1042 can be shaped to form an anterior surface of the contact lens 110. In some examples, the profile 1054 of the mold 1042 can be continuous without substantial interruptions.

[00114] FIG. 13 is a cross-sectional view of one embodiment of a mold 1042 with a liquid lens material 1052 according to the principles of the present disclosure. In some embodiments, the liquid lens material 1052 can be deposited into the profile 1054 of the mold.

[00115] The liquid lens material 1052 can be made from any material suitable for use in contact lenses. For example, the liquid lens material 1052 can be made of any silicone material and/or hydrogel material. Such material can be formed of polymers, such as tefilcon, tetrafilcon A, crofilcon, helfilcon A&B, mafilcon, polymacon, hioxifilcon B, lotrafilcon A, lotrafilcon B, galyfilcon A, senofilcon A, sifilcon A, comfilcon A, enfilcon A, lidofilcon B, surfilcon A, lidofilcon A, alfafilcon A, omafilcon A, vasurfilcon A, hioxifilcon A, hioxifilcon D, nelfilcon A, hilafilcon A, acofilcon A, bufilcon A, deltafilcon A, phemfilcon A, bufilcon A, perfilcon, etafilcon A, focofilcon A, ocufilcon B, ocufilcon C, ocufilcon D ocufilcon E, ocufilcon F, phemfilcon A, methafilcon A, methafilcon B, vilfilcon A, other types of polymers, monomers, or combinations thereof. These materials can include various combinations of monomers, polymers, and other materials to form the liquid lens material.

[00116] In one embodiment, the liquid lens material can be made of hydrogel polymers without any silicone. This can be desirable to increase the wettability of the contact lens. In another embodiment, the liquid lens material is made of silicone hydrogel material.

[00117] The contact lens 110 can be shaped and sized based on a variety of factors, including the shape and size of the user’s eye and various optical properties to be achieved by a central portion of the contact lens. In some examples, the total thickness of the contact lens 110 can be approximately 0.1 mm to approximately 0.14 mm. The thickness of the contact lens 110 can gradually vary at different locations on the contact lens 110. For example, the contact lens 110 can be thicker near the outer edge of the contact lens 110 than in the central portion of the contact lens 110.

[00118] FIGS. 14 and 15 depict cross-sectional views of a mold 1042 with a liquid lens material 1052 centrifugally spreading across a profile 1054 of the mold 1042 according to the principles of the present disclosure. In this example, the mold 1042 can be spun around a central axis 1066 within a spinning structure (1068, FIG. 15). The spinning structure 1068 can be rotated at a speed and in such a way that forms the desired posterior surface 1070 of the contact lens 110.

[00119] The spinning structure 1068 can include a central loading region that can receive the molds 1042 that contain the liquid lens material 1052. The central loading region can be formed by a glass tube, a metal tube, or another type of structure that can retain the molds 1042 in a stacked orientation. In examples in which actinic radiation is used as the curing agent, the spinning structure 1068 can have an opaque material, a semi-transparent material, or a transparent material that include a sufficient amount of openings to allow the actinic radiation into the central loading region. In the embodiment depicted in FIG. 15, the spinning structure 1068 can include multiple guide posts 1074 that retain the molds 1042 in a stacked orientation. The spinning structure 1068 can also include a region 1076 used to attach the spinning structure 1068 to a spinning driver, such as a motor.

[00120] The spinning structure 1068 can be programmed to rotate in a precise manner to form the desired posterior surface 1070 of the contact lens 110, which is the surface of the contact lens that is intended to contact the eye. A program that causes the spinning structure 1068 to rotate can be modified to create a desired profile for different users based on each user’s individual prescription. A curing agent can be applied to the liquid lens material 1052 while the spinning structure 1068 rotates the molds 1042. As a result, the contact lens 110 can be formed while the spinning structure rotates. In some embodiments, the contact lenses can be fully cured within the spinning structure. In other embodiments, the contact lens 110 can be fully cured over the course of multiple curing stages. For example, the contact lens can be cured in the spinning structure 1068 to a point in which the liquid lens material retains its shape but is not fully cured. At this stage, the mold with the contact lens can be removed from the spinning structure to finish curing in an environment that is cost effective. A spinning structure that is compatible with the principles described herein is described in U.S. Patent Publication 2012/0133064 issued to Stephen D. Newman. U.S. Patent Publication 2012/0133064 is herein incorporated by reference for all that is discloses.

[00121] The spin casting method of forming the curve of the posterior side of the contact lens can result in a continuous surface that is substantially free or entirely free of cavities or micro-cavities.

[00122] FIG. 16 depicts an example method 1600 for determining a contact lens recommendation. In one embodiment, the method 1600 can include analyzing 1602 a first characteristic of at least one biomarker from a first contact lens previously worn by a user during a first time period, comparing 1604 the first characteristic with a second characteristic of the at least one biomarker from the user, determining 1606 a change between the first characteristic and the second characteristic, and comparing 1608 the change with a database that correlates the change with the contact lens recommendation. The process block 1602 can be performed by the same entity ( e.g a processor) as that for the block 802 in FIG. 8. The process blocks 1604 through 1608 can be performed by the processor 515 (specifically, the biomarker and database comparer 555, in one example).

[00123] At block 1604, the first characteristic can be compared to a second characteristic. The first and second characteristics can be obtained from the same contact lens that is worn at different times. For example, the user can wear the contact lens on a first day and remove the contact lens at the end of the first day when the user has the biomarkers removed from contact lens. An analysis on the biomarkers can be done to obtain the first concentration, such as a first concentration of a first biomarker. On the second day, the user can place the contact lens back into his or her eye and remove the contact lens at the end of the day. The biomarker removal and analysis can also be performed. The second characteristic can be a different concentration of the first biomarker. Thus, the change can be an increased

concentration, a decreased concentration, another type of concentration, or combinations thereof.

[00124] In some embodiments, wherein the same contact lens is used to obtain the second set of biomarkers, the database can include specific correlations. In some embodiments, not all of the biomarkers can be removed from the contact lens during the first night of cleaning, therefore, the contact lens can be placed in the solution for a second night for cleaning. In other embodiments, biomarkers that remain on the contact lens after the first cleaning can block other biomarkers from attaching to the contact lens such that fewer biomarkers are retained the second night.

[00125] In some embodiments, a second set of biomarkers can be obtained using a fresh contact lens to avoid contamination from previous biomarkers. In those situations, lingering biomarkers from the previous cleaning time may not be an issue. The second set of biomarkers (e.g., a second set of biomarker characteristics) can be obtained from a second contact lens that is different than a first contact lens (the contact lens from which the first set of biomarker characteristics were obtained).

[00126] At block 1608, the difference between the first and second concentration levels can be compared to the database and correlated with a recommendation of a contact lens, the recommendation being correlated with the health condition of the user. The computing device can, with reference to the database, send, and the user (i.e. the mobile device, hand-held device, sensor, etc.) receive an indication of the recommendation. The database can include the correlated health condition. In this case, the computing device can send, and the user can receive, an indication of the correlated health condition.

[00127] In some embodiments, the first characteristic can be obtained at a different time than the second characteristic. In other embodiments, the first and second characteristics can be obtained within the same time period. For example, a first contact lens can be worn in a first eye and a second contact lens can be worn in a second eye, and the characteristics of the biomarkers can be analyzed and compared. In those situations where the characteristics are different, there can be a condition present in one of the eyes that is not in the other eye. [00128] The user can have an account associated with a hand-held device, a mobile device, a database, or associated with another computing device that stores at least some of the characteristics of the user’s biomarkers when data is sent to the database. These stored recordings can compile a health history of the user. The health history can be reviewed by the doctor to help diagnose health conditions, assist in making a treatment plan, assist in making a prevention plan, assist in helping diagnosis health conditions of relatives, determine other types of information, change contact lens recommendation, or combinations thereof. In some embodiments, a user’s eye can react to a contact lens by producing a certain biomarker over time. By comparing the user’s biomarker profile from earlier sessions of wearing that contact lens, a baseline profile can be obtained that is specific to that user. As the biomarker profile changes over time, the user can discover his or her eye is producing a higher level of a certain biomarker that is high for that user, despite the user’s concentration of that biomarker being within a normal concentration level of a significant portion of the population.

[00129] While the present exemplary system is described with reference to optical detection methods for determining biomarkers in a solution, the present exemplary system can also be performed with electrochemical and biochemical sensing detection methods for determining and detecting biomarkers in a solution.

[00130] In one embodiment, a method of generating a contact lens

recommendation, includes analyzing a characteristic of at least one biomarker from a contact lens; and comparing the characteristic with a database that correlates the characteristic with a contact lens recommendation.

[00131] The method can further include wherein the recommendation includes a contact lens material type.

[00132] The method can further include, wherein the contact lens material type comprises a hydrogel material.

[00133] The method can further include, wherein the contact lens material type comprises a silicone material.

[00134] The method can further include, wherein the contact lens material type comprises a silicone hydrogel material. [00135] The method can further include, wherein the database correlates the characteristic of the at least one biomarker to a health condition; and wherein the contact lens recommendation is based on the health condition.

[00136] The method can further include, wherein the health condition comprises an eye condition.

[00137] The method can further include, wherein the health condition comprises an eye comfort level.

[00138] The method can further include, wherein the health condition comprises a corneal strain level.

[00139] The method can further include, wherein the health condition comprises a dry eye level.

[00140] The method can further include, wherein the health condition comprises an allergic condition.

[00141] The method can further include, wherein the health condition comprises an infection.

[00142] The method can further include, wherein analyzing a least one biomarker contained on the contact lens comprises removing the at least one biomarker from the contact lens in an aqueous solution.

[00143] The method can further include, wherein the aqueous solution comprises a contact lens storage solution.

[00144] The method can further include, wherein analyzing the at least one biomarker contained on the contact lens comprises analyzing the aqueous solution containing the at least one biomarker.

[00145] The method can further include, wherein analyzing the aqueous solution comprises running a spectral analysis.

[00146] The method can further include, wherein analyzing the aqueous solution comprises applying an immunodiffusion process.

[00147] The method can further include, wherein analyzing the aqueous solution comprises taking a measurement with a sensor incorporated into a container holding the aqueous solution. [00148] The method can further include, wherein analyzing the aqueous solution comprises taking a measurement with a sensor incorporated into a mobile device.

[00149] The method can further include, wherein analyzing a least one biomarker contained on the contact lens comprises analyzing the contact lens within an ocular cavity of the user.

[00150] The method can further include, further comprising obtaining a measurement level based on an analysis of the at least one biomarker.

[00151] The method can further include, further comprising sending the measurement level to a remote device, a mobile device, a networked device, or combinations thereof.

[00152] The method can further include, further comprising comparing the measurement level with the database that correlates measurement levels with health conditions.

[00153] The method can further include, wherein the at least one biomarker comprises a protein.

[00154] The method can further include, wherein the at least one biomarker comprises an antibody.

[00155] The method can further include, wherein the at least one biomarker comprises an electrolyte level.

[00156] The method can further include, wherein the at least one biomarker comprises a sodium level.

[00157] The method can further include, wherein the at least one biomarker comprises a chloride level.

[00158] The method can further include, wherein the at least one biomarker comprises a potassium level.

[00159] The method can further include, wherein the at least one biomarker comprises a calcium level.

[00160] The method can further include, wherein the at least one biomarker comprises an iron level.

[00161] The method can further include, wherein the at least one biomarker comprises a lysozyme level. [00162] The method can further include, wherein the at least one biomarker comprises a lactoferrin level.

[00163] The method can further include, wherein the at least one biomarker comprises a lipocalin level.

[00164] The method can further include, wherein the at least one biomarker comprises an albumin level.

[00165] The method can further include, wherein the at least one biomarker comprises a cytokine level.

[00166] The method can further include, wherein the at least one biomarker comprises an enzyme level.

[00167] The method can further include, wherein the at least one biomarker comprises a lipid level.

[00168] The method can further include, wherein the at least one biomarker comprises a proteases level.

[00169] The method can further include, wherein the at least one biomarker comprises an immunoglobulin E level.

[00170] The method can further include, wherein the at least one biomarker comprises an immunoglobulin G level.

[00171] The method can further include, wherein the at least one biomarker comprises an immunoglobulin A level.

[00172] The method can further include, wherein the at least one biomarker comprises an immunoglobulin M level.

[00173] The method can further include, further comprising a removing the contact lens from an eye of the user.

[00174] The method can further include, wherein the contact lens has a

characteristic of having been worn by the user prior to analyzing the at least one biomarker.

[00175] A method of generating a contact lens recommendation, can include obtaining biomarkers from a contact lens previously worn by the user; analyzing at least one of the biomarkers to determine an eye condition of the user; and making a contact lens

recommendation based on the eye condition. [00176] The method can further include, obtaining a measurement level based on the analysis of the at least one biomarker.

[00177] The method can further include, sending the measurement level to a remote device, a mobile device, a networked device, or combinations thereof.

[00178] The method can further include, comparing the measurement level with a database that correlates measurement levels with eye conditions.

[00179] A method of making a contact lens recommendation can include comparing a characteristic of biomarkers from a contact lens previously worn by the user to an aggregated data that correlates characteristics of biomarkers with contact lens recommendations.

[00180] The method can further include, wherein the contact lens recommendation comprises a contact lens material type.

[00181] A method of receiving a contact lens recommendation can include dissolving a build-up on a contact lens into a solution; analyzing constituents of the build-up in the solution; sending at least one parameter derived from the analysis to a computing device; and receiving a contact lens recommendation from the computing device.

[00182] The method can further include, wherein the computing device comprises a mobile device.

[00183] The method can further include, wherein the computing device is in communication with a database that stores at least one correlation between characteristics of tear fluid and the contact lens recommendation.

[00184] The method can further include, wherein the build-up comprises a protein build-up.

[00185] A method of generating a contact lens recommendation can include analyzing a characteristic of at least one biomarker of a contact lens where a surface of the contact lens is substantially free of cavities; and comparing the characteristic with a database that correlates the characteristic with the contact lens recommendation.

[00186] A method of generating a contact lens recommendation can include analyzing a characteristic of at least one biomarker of a contact lens where a surface of the contact lens is substantially free of micro-cavities; and comparing the characteristic with a database that correlates the characteristic with the contact lens recommendation. [00187] A method of generating a contact lens recommendation can include analyzing a characteristic of at least one biomarker of a contact lens where a surface of the contact lens is substantially continuous; and comparing the characteristic with a database that correlates the characteristic with the contact lens recommendation.

[00188] A method of generating a contact lens recommendation can include analyzing a characteristic of at least one biomarker from an optical zone of a contact lens; and comparing the characteristic with a database that correlates the characteristic with the contact lens recommendation.

[00189] A method of generating a contact lens recommendation can include analyzing a characteristic of at least one biomarker of a contact lens made through spin casting; and comparing the characteristic with a database that correlates the characteristic with the contact lens recommendation.

[00190] A method of generating a contact lens recommendation can include analyzing a first characteristic of at least one biomarker from a first contact lens previously worn by a during a first time period; comparing the first characteristic with a second characteristic of the at least one biomarker from the user; determining a change between the first characteristic and the second characteristic; and comparing the change with a database that correlates the change with the contact lens recommendation.

[00191] The method can further include, wherein the second characteristic is obtained from the first contact lens.

[00192] The method can further include, wherein the second characteristic is obtained from a second contact lens that is different than the first contact lens.

[00193] The method can further include, wherein the second characteristic is obtained during a second time period that is different than the first time period.

[00194] The method can further include, wherein the second characteristic is obtained from a different eye of the user than the first characteristic.

[00195] A computing device can include a processor and a memory, wherein; the processor (i) obtains information which indicates a characteristic of at least one biomarker which is derived from a contact lens used by a user, and (ii) generates a recommendation of contact lens for the user based on the information. [00196] The computing device can further include, wherein the recommendation may include a contact lens material type, and the contact lens material type may comprise at least one of (i) a hydrogel material, (ii) a silicone material, and (iii) a silicone hydrogel material.

[00197] The computing device can further include, wherein the biomarker is correlated with a health condition of the user, and the processor generates the recommendation based on the health condition, and the health condition comprise at least one of, an eye condition, an eye comfort level, a corneal strain level, a dry eye level, an allergic condition, and an infection.

[00198] The computing device can further include, wherein the biomarker comprise at least one of, a protein, an antibody, an electrolyte level, a sodium level, a chloride level, a potassium level, a calcium level, an iron level, a lysozyme level, a lactoferrin level, a lipocalin level, an albumin level, a cytokine level, an enzyme level, a lipid level, a proteases level, an immunoglobulin E level, an immunoglobulin G level, an immunoglobulin A level, and an immunoglobulin M level.

[00199] The computing device can further include, wherein the processor (i) obtains (a) information which indicates a characteristic of at least one biomarker which is derived from a contact lens used by the user and (b) information which indicates a characteristic of the biomarker which is derived from another contact lens used by the user, and (ii) generates a recommendation of contact lens for the user based on both of the information (a) and the information (b).

[00200] The computing device can further include, wherein the processor (i) obtains (a) information which indicates a characteristic of at least one biomarker which is derived from a contact lens worn by the user for a time period and (b) information which indicates a characteristic of the biomarker which is derived from the contact lens worn by the user for another time period, and (ii) generates a recommendation of contact lens for the user based on both of the information (a) and the information (b).

[00201] The computing device can further include, wherein the processor (i) obtains (a) information which indicates a characteristic of at least one biomarker which is derived from a contact lens worn on a first eye of the user and (b) information which indicates a characteristic of the biomarker which is derived from a contact lens worn on a second eye of the user, and (ii) generates a recommendation of contact lens for the user based on both of the information (a) and the information (b).

[00202] A non-transitory computer readable recording medium can store therein a program for causing the computer to execute the steps of (i) obtaining information which indicates a characteristic of at least one biomarker which is derived from a contact lens used by a user, and (ii) generates a recommendation of contact lens for the user based on the information.

[00203] Unless otherwise indicated, all numbers or expressions, such as those expressing dimensions, physical characteristics, etc., used in the specification (other than the claims) are understood as modified in all instances by the term“approximately.” At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the claims, each numerical parameter recited in the specification or claims which is modified by the term “approximately” should at least be construed in light of the number of recited significant digits and by applying ordinary rounding techniques.

[00204] In addition, all ranges disclosed herein are to be understood to encompass and provide support for claims that recite any and all subranges or any and all individual values subsumed therein. For example, a stated range of 1 to 10 should be considered to include and provide support for claims that recite any and all subranges or individual values that are between and/or inclusive of the minimum value of 1 and the maximum value of 10; that is, all subranges beginning with a minimum value of 1 or more and ending with a maximum value of 10 or less (e.g., 5.5 to 10, 2.34 to 3.56, and so forth) or any values from 1 to 10 (e.g., 3, 5.8, 9.9994, and so forth).

Claims

WE CLAIM:

1. A method of generating a contact lens recommendation, comprising:

analyzing an aqueous solution to determine a characteristic of at least one biomarker within the aqueous solution, the aqueous solution being positioned within a container configured to house at least one contact lens;

receiving data relative to the characteristic at a database;

comparing the data with a plurality of biomarker characteristics stored within the database, the data being compared with the plurality of biomarker characteristics; and

generating a contact lens recommendation based on the comparison.

2. The method of claim 1, wherein analyzing the aqueous solution further comprises:

using a measuring device comprises emitting light through the aqueous solution; and conducting a spectral analysis.

3. The method of claim 1, wherein the at least one biomarker comprises a protein build-up on a surface of the at least one contact lens.

4. The method of claim 1 further comprising predicting a health condition of the user based on the comparison.

5. The method of claim 2, wherein the measuring device includes a sensor incorporated into a container holding the aqueous solution.

6. The method of claim 2, wherein the measuring device includes a sensor incorporated into a mobile device.

7. The method of claim 1, wherein comparing the data with the plurality of biomarker characteristics stored within the database includes sending the data to a remote device, a mobile device, a networked device, or a combination thereof.

8. The method of claim 1, wherein the at least one biomarker is deposited into the aqueous solution by submerging the contact lens into the aqueous solution.

9. A method of generating a contact lens recommendation, comprising:

providing an aqueous solution configured to receive a contact lens from the user;

emitting light through the aqueous solution using a light source;

measuring at least one characteristic of the light source with a sensor;

sending data related to the at least one characteristic to a database; and

comparing the data to the contents of the database to generate a contact lens

recommendation.

10. The method of claim 9, wherein the light source emits isolated predetermined wavelengths of light through the aqueous solution.

11. The method of claim 9, wherein the light source emits a broad spectrum of wavelengths and the sensor includes at least one filter.

12. The method of claim 9, wherein measuring further comprises utilizing Raman spectroscopy.

13. The method of claim 9, wherein the database is configured to organize and manipulate the data after the data has been received by the database.

14. The method of claim 13 further comprising storing the data within the database.

15. The method of claim 9 further comprising comparing the data to the contents of the database to determine a health condition of the user.

16. A method of generating a contact lens recommendation, comprising:

analyzing the aqueous solution using a measuring device after a first duration of time to determine a first characteristic of a first biomarker within the aqueous solution; analyzing the aqueous solution using the measuring device after a second duration of time to determine a second characteristic of a second biomarker within the aqueous solution; determining a change between the first and second characteristics;

comparing the change with a database that correlates the change between the first and second characteristics with recommended contact lenses; and

generating a contact lens recommendation based on the comparison.

17. The method of claim 16, wherein analyzing the aqueous solution includes emitting light through the solution and measuring a light characteristic of the light using Raman spectroscopy.

18. The method of claim 16, wherein the change between the first and second characteristics is a change in concentration of the first biomarker within the aqueous solution or a rate of concentration change of the first biomarker within the aqueous solution.

19. The method of claim 16, wherein the first duration of time and the second duration of time are equal in duration.

20. The method of claim 16 further comprising replacing the aqueous solution with uncontaminated aqueous solution between the first duration of time and the second duration of time.

21. A computing device comprising a processor and a memory, wherein the processor: obtains information which indicates a characteristic of at least one biomarker which is derived from a contact lens used by a user; and

generates a recommendation for a contact lens for the user based on the information.

22. The computing device of claim 21, wherein:

the recommendation includes a contact lens material type; and

the contact lens material type comprises at least one of a hydrogel material, a silicone material, a silicone hydrogel material, a rigid lens material, a soft contact lens material, a daily disposable contact lens material, an extended wear contact lens material, and a rigid gas permeable contact lens material.

23. The computing device of claim 21, wherein:

the characteristic is correlated with a health condition of the user;

the processor generates the recommendation based on the health condition; and the health condition comprises at least one of an eye condition, an eye comfort level, a corneal strain level, a dry eye level, an allergic condition, and an infection.

24. The computing device of claim 21, wherein the biomarker comprises at least one of a protein, an antibody, an electrolyte level, a sodium level, a chloride level, a potassium level, a calcium level, an iron level, a lysozyme level, a lactoferrin level, a lipocalin level, an albumin level, a cytokine level, an enzyme level, a lipid level, a proteases level, an osmolarity, a matrix metalloproteinase-9 level, an immunoglobulin E level, an immunoglobulin G level, an immunoglobulin A level, and an immunoglobulin M level.

25. The computing device according to claim 21, wherein the processor:

obtains a first contact lens information which indicates a characteristic of at least one biomarker which is derived from a first contact lens used by the user, and a second contact lens information which indicates a characteristic of the biomarker which is derived from a second contact lens used by the user; and

generates a recommendation for a contact lens for the user based on both of the first contact lens information and the second contact lens information.

26. The computing device according to claim 21, wherein the processor:

obtains a first time-based information set that indicates a characteristic of at least one biomarker which is derived from a contact lens worn by the user for a first period of time, and a second time-based information set that indicates a characteristic of the at least one biomarker which is derived from the contact lens worn by the user for a second period of time; and

generates a recommendation for a contact lens for the user based on both of the first time- based information set and the second time-based information set.

27. The computing device according to claim 21, wherein the processor:

obtains a first eye information set that indicates a characteristic of at least one biomarker that is derived from a contact lens worn on a first eye of the user, and a second eye information set that indicates a characteristic of the at least one biomarker that is derived from a contact lens worn on a second eye of the user; and

generates a recommendation for a contact lens for the user based on both of the first eye information set and the second eye information set.

28. A non-transitory computer readable recording medium storing therein a program for causing the computer to:

obtain information that indicates a characteristic of at least one biomarker that is derived from a contact lens used by a user, and

generate a recommendation for a contact lens for the user based on the information.