GB2622203A

GB2622203A - Point-of-care device for monitoring medication adherence in subject, and system and method for delivering incentivized medication adherence and opioid

Info

Publication number: GB2622203A
Application number: GB2212910.0A
Authority: GB
Inventors: Elarabi Hesham
Original assignee: Individual
Current assignee: Individual
Priority date: 2022-09-05
Filing date: 2022-09-05
Publication date: 2024-03-13
Also published as: GB202212910D0

Abstract

A point-of-care device 100 for monitoring medication adherence in a subject. The device comprises a light source 102; a first filter 104 for filtering light at a specific excitation wavelength; a beam splitter 106 configured to split a beam of light into two beams, wherein first beam is received by a first photomultiplier tube 108 configured to detect a specific excitation wavelength, and second beam is received by a sample cuvette 110. The device comprises a second filter 112 for receiving light emitted by the sample cuvette and filtering light at a specific emission wavelength; a second photomultiplier tube 114 configured to detect specific emission wavelength of light; and a detector 116 for detecting medication concentration in blood sample of subject based on detected specific emission wavelength of light. The medication may be an opioid, and the blood sample may be a venous or capillary blood sample.

Description

POINT-OF-CARE DEVICE FOR MONITORING MEDICATION ADHERENCE IN

SUBJECT, AND SYSTEM AND METHOD FOR DELIVERING INCENTIVIZED

MEDICATION ADHERENCE AND OPIOID ABSTINENCE THERETO

ILCHNICAL FIELD

The present disclosure relates generally to clinical management of illicit substance misuse and more specifically, to a point-of-care device for monitoring a medication adherence in a subject. The present disclosure also relates to a system and a method for delivering incentivized medication adherence and opioid abstinence in a subject.

BACKGROUND

Opioid Use Disorder (OUD), amongst other substance use disorders, is a global public health concern associated with high disease burden including mortality. Pharmacotherapy using buprenorphine and similar opioid agonist medications is among first line recovery-oriented treatment. However, access to buprenorphine and similar opioid agonist medications is limited to only 10% of individuals with OUD due to concerns over adherence, diversion and rising costs.

Notably, poor adherence to medication (buprenorphine and similar opioid agonist medications) increases the risk of relapse, hence optimizing adherence will contribute to optimal outcomes. Generally, patients are required to receive a daily-supervised (in-person) medication administration, at a pharmacy or a clinic, which is associated with high treatment dropouts and logistical challenges similar to those demonstrated during the COVID-19 lock-down.

An alternative strategy to mitigate poor medication adherence and high treatment dropouts, some countries provide onsite-supervised treatment at a lower frequency ranging from three-times weekly with long-acting injectable formulations of medication or take-home prescription to a maximum of two-week take-home prescriptions. Moreover, the injectable long acting formulations of medication are associated with high cost while their effectiveness remains equivocal.

Furthermore, such alternative strategy includes regular blood tests to be performed on subjects to assess medication adherence. In this regard, conventionally, blood samples are collected via a venous line from various subjects by an invasive procedure (painful) and sent to a laboratory to measure buprenorphine blood levels with a turn-around time of 3-to-5 days to report results.

However, the need for a highly specialized, resource intensive and expensive laboratory service with such extended turn-around time tends to limit the effectiveness of the conventional process and serves as a significant barrier to extend to mainstream services. Therefore, in order to facilitate the implementation of the general process and expand its application, it is important to have reliable, pragmatic and rapid alternative to measure buprenorphine blood levels.

Recently, tele-medicine management and real-time observation of medication administration have been explored as promising approaches with limited availability of high-quality evidence. In addition to the approaches related to adherence, regular monitoring including medication count and random call-back of medications were reported as attempts to minimize medication diversion.

However, the aforementioned approaches fail to provide substantial medication adherence rates.

Therefore, in the light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks associated with conventional ways and provide an objective measure to assess medication adherence.

SUMMARY

The present disclosure provides a point-of-care device for monitoring a medication adherence in a subject. The present disclosure also provide a system for delivering incentivized medication adherence and opioid abstinence in a subject. The present disclosure also provides a method for delivering incentivized medication adherence and opioid abstinence in a subject. The present disclosure seeks to provide a solution that overcomes at least partially the existing problems

encountered in prior art.

In a first aspect, an embodiment of the present disclosure provides a point-of-care device for monitoring a medication adherence in/of a subject, the point-of-care device comprising: -a light source for emitting a light; - a first filter for receiving the light emitted by thc light source and filtering the light at a specific excitation wavelength; - a beam splitter configured to split a beam of light into two beams, wherein -a first beam from amongst the two beams is received by a first photomultiplier tube configured to detect the specific excitation wavelength of the first beam, and -a second beam from amongst the two beams is received by a sample cuvette; - a second filter for receiving the light emitted by the sample cuvette and filtering the light at a specific emission wavelength; - a second photomultiplier tube configured to detect the specific emission wavelength of the light; 5 and -a detector for detecting a medication concentration in blood sample of the subject based on the detected specific emission wavelength of the light.

In a second aspect, an embodiment of the present disclosure provides a system for delivering incentivized medication adherence and opioid abstinence in a subject, the system comprising: -a point-of-care device of the aforementioned first aspect; and - a pharmacokinetic model, associated with the point-of-care device, configured to - receive a data from the point-of-care device; and - assess medication adherence based on the data received from the point-of-care device.

In a third aspect, an embodiment of the present disclosure provides a method for delivering is incentivized medication adherence and opioid abstinence in a subject, the method comprising: - stabilizing the subject on a medication concentration; - obtaining data from the subject using a point-of-care device of the aforementioned first aspect; and - altering the medication take-home doses of the subject based on the data obtained, wherein the data obtained is associated with the medication adherence that is different from a predefined threshold.

It is to be appreciated that all the aforementioned implementation forms can be combined. It has to be noted that all devices, elements, circuitry, units, and means described in the present application could be implemented in the software or hardware elements or any kind of combination thereof All steps which are performed by the various entities described in the present application as well as the functionalities described to be performed by the various entities are intended to mean that the respective entity is adapted to or configured to perform the respective steps and functionalities. Even if, in the following description of specific embodiments, a specific functionality or step to be performed by external entities is not reflected in the description of a specific detailed element of that entity that performs that specific step or functionality, it should be clear for a skilled person that these methods and functionalities can be implemented in respective software or hardware elements, or any kind of combination thereof It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments construed in conjunction with the appended claims that follow.

It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those skilled in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.

Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein: FIG. 1 is a schematic illustration of a point-of-care device for monitoring incentivized medication adherence and opioid abstinence in a subject, in accordance with an embodiment of the invention; FIG. 2 is a schematic illustration of a system for monitoring incentivized medication adherence and opioid abstinence in a subject, in accordance with an embodiment of the invention; FIG. 3 is a flowchart depicting steps of a method for monitoring incentivized medication adherence and opioid abstinence in a subject, in accordance with an embodiment of the invention; FIG. 4 is a flowchart illustrating an algorithm for allocation a subject to a treatment based on response prediction using an elimination rate constant, in accordance with an embodiment of the invention; and FIG. 5 is an exemplary reference calibration curve of a variation of a concentration of 5 known samples with respect to a response of the detector, in accordance with an embodiment of the invention.

In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.

DETAILED DESCRIPTION OF EMBODIMENTS

The following detailed description illustrates exemplary aspects of the disclosed embodiments and ways in which they can be implemented. Although some modes of carrying out the aspects of the disclosed embodiments have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practising the aspects of the disclosed embodiments are also possible.

In a first aspect, an embodiment of the present disclosure provides a point-of-care device for monitoring a medication adherence in/of a subject, the point-of-care device comprising: -a light source for emitting a light; -a first filter for receiving the light emitted by the light source and filtering the light at a specific excitation wavelength; -a beam splitter configured to split a beam of lit-Mt into two beams, wherein -a first beam from amongst the two beams is received by a first photomultiplier tube configured to detect the specific excitation wavelength of the first beam, and -a second beam from amongst the two beams is received by a sample cuvette; -a second filter for receiving the light emitted by the sample cuvette and filtering the light at a specific emission wavelength; - a second photomultiplier tube configured to detect the specific emission wavelength of the light; and -a detector for detecting a medication concentration in blood sample of the subject based on the detected specific emission wavelength of the light.

In a second aspect, an embodiment of the present disclosure provides a system for delivering incentivized medication adherence and opioid abstinence in a subject, the system comprising: - a point-of-care device of the aforementioned first aspect; and -a pharmacokinetic model, associated with the point-of-care device, configured to - receive a data from the point-of-care device; and -assess medication adherence based on the data received from the point-of-care device.

In a third aspect, an embodiment of the present disclosure provides a method for delivering incentivized medication adherence and opioid abstinence in a subject, the method comprising: -stabilizing the subject on a medication concentration; -obtaining data from the subject using a point-of-care device of the aforementioned first aspect; 15 and - altering the medication take-home doses of the subject based on the data obtained, wherein the data obtained is associated with the medication adherence that is different from a predefined threshold.

The present disclosure provides the aforementioned device, system and method for monitoring a medication adherence in/of a subject. Suitably, the point-of-care device eliminates the need for a resource intensive, highly specialized and expensive laboratory toxicology service that reports results within an extended turnaround time. Moreover, the point-of-care device contributes to optimizing the effectiveness of the clinical decisions, and provides a practical alternative to venous blood collection via capillary blood (finger stick) by collecting peripheral or capillary blood sample from the subject. Moreover, the point-of-care device measures medication concentration in the blood sample within 5 -10 minutes replacing expensive and complex toxicology laboratory test with a turn-around time of 3 to 5 days. Providing rapid measures of medication concentration facilitates rapid assessment of the medication adherence and hence effective clinical response.

Furthermore, the point-of-care device is a cost-effective objective measure to assess medication adherence by providing access to cost-effective buprenorphine treatment.

Herein, the term "monitoring" refers to a regular observation and recording of various activities (such as consumption of medication or drug, physical activities, and the like) performed by the subject to ensure quality of life and determine the real-time medical data thereof as a result of said activities. Herein, the term "monitoring medication adherence" refers to a clinically effective monitoring process to enable contingent access to increasing take-home medication supplies by the subject at an outpatient or an ambulatory care service. It will be appreciated that such monitoring is achieved by consideration of various physiological tests, such as blood sample tests, urine toxicological screens (or urine drug screening (UDS), and so on. Notably, LIDS is a qualitative test that gives an indication of recent medication use Herein, the term "medication adherence" refers to a prescribed use of effective medications that can reverse the opioid use disorders (DUD). Throughout the present disclosure, the term "opioid" refers to a class of drugs, naturally occurring or synthetic substances, that have morphine-like activity. Typically, the opioids include heroin, fentanyl, oxycodone, hydrocodone, codeine, morphine, and the like. Typically, the opioids interact with opioid receptors (such as mu, chi, sigma) on nerve cells. It will be appreciated that opioid pain relievers, when take in prescribed amount by doctors, is safe to use, while misuse thereof for other effects (such as euphoria) is considered to be opioid use disorders (DUD), namely, addiction and/or overdose that may lead to deaths.

In an embodiment, the medication is an opioid agonist selected from at least one of: a buprenorphine, a methadone, or an opioid agonist such as a naltrexone, a naloxone. Typically, the opioid agonist (morphine-like) and the opioid agonist (nalorphine-like) are heterogenous group of drugs that attach to the opioid receptors and reverses and blocks the effects of opioids. Herein, the opioid agonist may be an opioid full agonist or an opioid partial agonist. Notably, buprenorphine and methadone are the opioid partial agonists. Optionally, a combination of opioid agonistantagonist may be used to treat DUD. Notably, a combination of buprenorphine and naloxone and an extended release naltrexone are effective medications for treating opioid addiction.

In an embodiment, the medication adherence in the subject is associated with a measurement of a concentration of the medication in a blood sample from the subject. Herein, the term "subject" refers to a person, such as a patient, an elderly person, a worker, a child, a sportsperson, and the like, with OUD, voluntarily seeking treatment. Optionally, the subject could be monitored when in, a home, a care home, a hospital, a workplace, an isolation, travelling (on-the-move), and the like based on a prescribed treatment or from a past medical history of the subject. Optionally, the subject may be monitored by a caregiver. Herein, the term "caregiver" refers to a person such as a family member, a guardian, a doctor, a medical practitioner, and the like. For example, the subject is a patient in a hospital and a nurse is the caregiver taking care thereof Optionally, the subject is a patient in a care home or their home, and a care home manager or a family member is a caregiver to such a care home patient.

In an embodiment, the medication concentration comprises a total medication concentration and a free medication concentration. The total medication concentration typically includes the protein-bound medication and the free (or unbound) medication concentration in the blood sample (serum or plasma). Notably, the protein-bound medication is inactive and only the free medication can bind with the receptor (such as the opioid receptor) for providing the intended pharmacological action. Therefore, the free medication concentrations correlate to therapeutic effects better than total medication concentrations, for both small and large molecules. It will be appreciated that the total medication concentration and the free medication concentration may be determined using any of the techniques known to a person skilled in the art, such as, for example, a fluorescent detector.

In an embodiment, the blood sample is a venous blood sample or a capillary blood sample. Notably, the venous blood sample is generally obtained from peripheral veins by a direct puncturing of the vein using a syringe, a vascular access point-of-care device (\TAD), and the like. The venous blood sample is the specimen of choice for routine laboratory tests. The capillary blood sample is collected from capillary beds of the circulatory system by a dermal puncturing of fingertip or heel. The capillary blood sample is the specimen of choice for most point-of-care devices.

The term point-of-care device as used herein is a bench-top portable point-of-care device used to measure medication concentrations in the blood sample of the subject. In an embodiment, the point-of-care device is configured for monitoring the medication adherence within a time period of 5 to 10 minutes. In this regard, the point-of-care device is configured to receive the blood sample, preferably the capillary blood sample, from the subject for analysis and beneficially delivers the results within a period of 5-I 0 minutes. This is mainly attributed to the point-of-care device's high sensitivity and selectivity to the medication, such as burprenorphine. It will be appreciated that the medication concentration, such as burprenorphine concentration, generated by the point-of-care device shows a strong correlation (at least 0.89) with corresponding concentrations generated by standard reference platforms, such as Liquid Chromatography with mass spectrometry (LC-MS) instruments.

The point-of-care device comprises the light source for emitting a light. The term "light source" as used herein refers to an arrangement for providing optimal light in the point-of-care device. Optionally, the light source may require 0-10V power for the operation thereof. Optionally, the light source includes at least one of a light emitting diode (LED), laser lights, a xenon lamp, and so on, wherein the light source in operation regulates at least one of: a light intensity, a light quality, a wavelength of light, and a duration of light exposure.

In an embodiment, the light source is a xenon lamp. Typically, the xenon lamp is a type of gas discharge lamp that produces light (normally, bright white light) by passing electricity through ionized xenon gas at high pressure. Notably, the xenon lamp generates light in ultraviolet (UV) range of electromagnetic spectrum (i.e. 10-400 nm).

In this regard, the light emitted by the light source is filtered at the specific excitation wavelength at the first filter to hit the beam splitter to result in two beams, the first beam and the second beam to hit the first photomultiplier tube (namely, the excitation wavelength detector) and the sample cuvette, respectively. In this regard, the electron sample is excited into a higher orbit number and then stabilized to emit light which is received by the blood sample in the sample cuvette. It will be appreciated that the first filter and the beam splitter are designed to pass or reject wavelengths of light with great selectivity with high transmission rate. Optionally, the first photomultiplier tube receives the first beam to measure intensity of the first beam at the specific excitation wavelength. The intensity of the first beam at the specific excitation wavelength is used as a reference value. Optionally, the second beam is received by the sample cuvette to cause excitation of the blood sample. The excitation of the blood sample results in emission of energy (i.e., emission of the light at a specific wavelength). Notably, the second filter allows the light (from the sample cuvette) to pass through at the specific emission wavelength to hit the second photomultiplier. Optionally, a ratio of the intensity of the first beam at the specific excitation wavelength received at the first photomultiplier and intensity of the light at the specific emission wavelength received at the second photomultiplier is obtained to calculate the medication concentration in the blood sample The capillary blood sample may be mixed with a reagent in a cuvette that is inserted in the pointof-care device. In this regard, the blood sample is mixed with a suitable reagent wherein selection of the most suitable reagent will be performed according to the best fit with the terminal chemical functional groups in the monitored medication structure. Optionally, a common set of immunoassay reagents may be used. Notably, three basic components of a competitive immunoassay reagent are an antibody, a labeled analyte, and an unlabeled analyte. Moreover, a Precipitating Reagent allows separation of bound ligand-antibody complexes from free ligand and in the process leaving the antibody to remain unbound. Optionally, a reagent containing polyethylene glycol (PEG) and sodium azide in phosphate buffer having a pH of 6.8 may be used.

The emitted light from the sample cuvette is again filtered at specific wavelength and quantified by the second photo-multiplier tube (namely, emission wavelength detector). The detector for detecting light energy will provide results proportional to the concentration of medication in the blood sample in the sample cuvette. Notably, the light from the sample cuvette is received by the detector to detect the medication concentration in the blood sample based upon the specific emission wavelength of the light. A response provided by the detector is directly proportional to the medication concentration in the blood sample. Optionally, the medication concentration is measured by making a reference calibration curve of known samples. An exemplary reference calibration curve is illustrated in FIG. 5 as described later in detailed description of drawings. In the reference calibration curve, a concentration of known samples is represented along a horizontal axis and the response is represented along a vertical axis. The response and the concentration of the known samples are plotted along a line. Herein, the medication concentration in the blood sample can be obtained by plotting points on the line and intercept on the horizontal axis.

In an embodiment, the point-of-care device is further configured to predict alike] hood of response to the medication. The term "likelihood of response to the medication" as used herein refers to a tentative response of a subject's body for a given medication consumed over a period of time. Herein, the likelihood of response to the medication refers to the contribution of medication to the subjecf s medication adherence and/or abstinence to opioids. Notably, the medication dose prescribed, the number of times dose prescribed consumed, the data received from the point-ofcare device, and corresponding laboratory tests provide information about the medication adherence that influence the likelihood of response to the medication. Optionally, the likelihood of response to the medication may be determined per day based on the medication adherence of the subject. Optionally, the likelihood of response to the medication is obtained by calculating a variation of an actual concentration of the buprenorphine with the predicted concentration using a pharmacokinetic equation as follows: Cpss = Co. e-kt Where: Co is a peak concentration of the buprenorphine in the subject. The term "peak concentration" refers to the concentration just after administrating the buprenorphine to the subject.

Cpss is a trough concentration of the buprenorphine in the subject. The term "trough concentration" refers to a lowest concentration (namely, predicted concentration) immediately before a second dose is provided to the subject.

k is the Elimination rate constant (ELR). The term "elimination rate constant" refers to a fraction of the buprenorphine eliminated from the subject per unit of time. t is a time interval between measuring the peak concentration and the trough concentration.

In a case, the variation of more than 20 percent between the actual concentration of the buprenorphine with the predicted concentration indicates that the subject's medication adherence is high. In another case, the variation within 20 percent indicates that the subject's medication adherence is low with the buprenorphine.

In an embodiment, the point-of-care device is further configured to generate a predictive model to predict a personalized treatment for the subject. In this regard, based on the likelihood of response to the medication, the point-of-care device is configured to predict a treatment algorithm that can be adopted to allocate the subject to at least one treatment, such as a treatment comprising buprenorphine and naloxone (BURT\IX) medications. Optionally, the predictive model is generated by examining a correlation between the ELK of the buprenorphine and a negative opioid screen. The term "opioid screen" refers to opioid testing in the subject. Optionally, the predictive model that is used to predict the personalized treatment is a regression model. The regression model has a prediction power of determining the likelihood of response to the medication up to 65% at a p-value of less than 0.001. The correlation between the ELR of the buprenorphine and the negative opioid screen is determined using a mathematical formula as follows: 104.6 -415.32 BUP ELR -4132.8 BUP ELR2 -11580.33 BUP is a value of negative opioid screen in the subject in response to the buprenorphine. ELR is the elimination rate constant of the buprenorphine.

In an embodiment, the personalized treatment for a given subject is associated with a reduction in illicit opioid use in the given subject. In this regard, using the likelihood of response to the medication, the treatment algorithm allocates the subject to BURNX or to an alternative course of treatment depending on a pre-set threshold of opioid-negative UDS percentage. Optionally, the personalized treatment of the subject is determined based on the opioid negative screen of the subject. Optionally, the pre-set threshold of opioid-negative UDS percentage depends on the medication administered in the subject. In a case, if a required value of the opioid negative screen is obtained for a required medication administered to the subject, within a required time duration, the subject is placed on that medication. In another case, if the required value of the opioid negative screen is not adhered upon administration of the required medication, the subject is considered for another medication. For example, the buprenorphine may show 75 percent opioid negative screen within 16 weeks of the buprenorphine administration and the predictive model shows that the subject may attain greater than or equal to the 75 percent opioid negative screen, then the subject may be placed on the buprenorphine medication, else the subject may be considered for different medication other than the buprenorphine. In an embodiment, the point-of-care device further comprises the database to store a data, wherein the data comprises: a medication concentration, an estimated elimination rate of the medication, a subject detail. It will be appreciated that the pointof-care device has a data component for each subject's visit, medication concentration and estimated elimination rate that may be stored in the database associated with the point-of-care device. Herein, the estimated elimination rate of the medication relates to rate at which half of the concentration of medication is eliminated from the body of the subject. Herein, the subject detail may comprise a name, an age, an addiction, a term of such addiction, any prior treatment history, prescribed treatment, associated laboratory tests, and so on. Optionally, the point-of-care device also includes a processor (not shown) to control functions of all the components (as described above) of the point-of-care device and to help in acquiring the aforesaid information. Additionally, optionally, the processor acts as an interface between the point-of-care device and the database.

Optionally, as described herein above, the estimated elimination rate of the medication is determined based upon a concentration of the opioids in the blood sample. Greater the concentration of the opioid in the blood sample, greater is the estimated elimination rate of the medication, and vice versa. The present disclosure also relates to the system as described above.

Various embodiments and variants disclosed above apply mutatis mutandis to the system.

Notably, the stored data in the database associated with the point-of-care device is fed into the pharmacokinetic model, associated with the point-of-care device, configured to assess the medication adherence, and an exploratory predictive model that identifies subjects who are more likely to be responsive to the prescribed or predicted treatment.

Suitably, the system is a comprehensive solution that is composed of a novel solution for clinical management and treatment algorithm of patients with opioid use disorder (OUD) maintained on buprenorphine (or other similar) medications at an outpatient or ambulatory care service using a point-of-care test (POCT) referred to as 'the point-of-care device' to monitor medication concentrations in the blood. The system also predicts the response to medication treatment early in the treatment process which contributes to precision and personalized treatment that allocates patients to the appropriate medication.

In an embodiment, the data received from the point-of-care device comprises a medication concentration, an estimated elimination rate of the medication, a subject detail.

In an embodiment, the pharmacokinetic model is further configured to predict a likelihood of response to the medication.

In an embodiment, the pharmacokinetic model is further configured to predict a personalized treatment for the subject.

In an embodiment, the pharmacokinetic model is further configured to create a calibration curve between a medication concentration obtained from laboratory testing and a medication concentration obtained from the point-of-care device, to assess medication adherence. In this regard, the calibration curve serves to compare the data obtained from conventional laboratory testing and data obtained from the point-of-care device's predictive model, to train the predictive model further for assessing medication adherence in the subject. Optionally, the calibration curve is obtained by optimizing a fluorescence reagent, the specific excitation wavelength, the specific emission wavelength. The calibration curve can be plotted by determining the medication concentration in the blood sample of the subject in the laboratory and using the point-of-care device. Optionally, parameters of the calibration curve are determined based on a required range of medication concentration and a feasible range of detection of the medication concentration. The present disclosure also relates to the method as described above Various embodiments and variants disclosed above apply mutatis mutandis to the method.

Suitably, the novel method addresses poor medication adherence and abstinence from illicit substance (such as opioid) use. The method provides a dynamic individualized management of the patients that significantly enhances treatment outcomes related to OUD, particularly reduction in illicit opioid use. The method includes an objective measure of medication adherence (medication levels in the blood) and uses urine toxicological screens to adjust take-home prescriptions (unsupervised) of up to 4-weeks compared to daily supervised (in-person) dosing. The novel method is significantly more effective than the conventional methods (treatment-as-usual). The novel method is a cost-effective ambulatory care medication treatment management method of medication-based treatment for OUD with minimal concerns over diversion. Moreover, novel method simulates and provides for contingency management, which is an effective behavioral intervention, established for management of OUD. Furthermore, medication concentrations are included in a pharmacokinetic model to monitor level of medication adherence and predict likelihood of response to the medication.

In this regard, the method comprises feeding individualized subject data stored in the database of the point-of-care device into the pharmacokinetic model to assess medication adherence in the subject and training the predictive model that identifies subjects who are more likely to be responsive to a prescribed treatment. Early prediction of response will guide treatment, i.e. whether to continue on the prescribed medication, for example buprenorphine, or switch to an alternative treatment, for example buprenorphine and naloxone (BTJP/NX) medications, early in the treatment process.

Moreover, the step of stabilizing the subject on a medication concentration is achieved in supervised mode initially in an out-patient or ambulatory care service. The data stored in the database of the point-of-care device is used to continue the subject on the prescribed treatment or switch to an alternate treatment if the medication adherence of the subject varies significantly from the subject's predicted medication concentration, namely, by the predefined threshold. Herein, the term "predefined threshold" refers to a pre-set maximum allowable count (or number) of the one or more anomalous events, herein medication adherence, characterizing a normal behavior. The predefined threshold may be associated with the subject's predicted medication concentration.

In an embodiment, the method is selected from a non-supervised mode or a semi-supervised mode. It will be appreciated that the non-supervised mode refers to a stage where the subject is provided with the medication take-home doses based on their medication adherence and/or opioid abstinence for a set period of time. The semi-supervised mode refers to a stage where the subject is required to visit clinics or laboratory to have the laboratory testing done on venous blood samples and urine samples (for UDS) for potential assessment of medication adherence to the medication take-home doses and/or opioid abstinence for a the prescribed period of time.

In an embodiment, the method is further configured to predict a likelihood of response to the medication.

In an embodiment, the method is further configured to predict a personalized treatment for the subject.

In an embodiment, the method further uses urine toxicological screens and a blood testing to adjust the personalized treatment for the subject.

In an embodiment, the method comprises prescribing medication for a period of 7 to 28 days in the non-supervised mode or the semi-supervised mode. In this regard, medication, such as buprenorphine, take-home doses are increased from 7-days, to 14-days, to 21-days to a maximum of 28-days according to defined procedures.

In an embodiment, the method comprises -maintaining the subject on a medication in a five-day outpatient mode, wherein the five-day outpatient mode comprises supervised dosing and/or at least three urine toxicological screen; -prescribing, to the subject, a medication for a seven-day unsupervised mode if the urine toxicological screen in the five-day outpatient mode is negative, wherein the seven-day unsupervised comprises supervised dosing and/or at least three urine toxicological screen; -prescribing, to the subject, a medication for a fourteen-day unsupervised mode if the urine toxicological screen in the seven-day unsupervised mode is negative, wherein on a fourteenth day of the fourteen-thy unsupervised mode, the method comprises (a) requiring the subject not to take the medication on a test day; (b) collecting a venous blood sample from the subject for laboratory testing of the medication concentration in the blood sample of the subject; (c) prescribing, to the subject, a medication for another fourteen-day unsupervised mode; and (d) repeating steps (a) to (b) and comparing the medication concentration in the blood sample of the subject from laboratory testing on the fourteenth day with the medication concentration obtained from the point-of-care device estimated on the fourteenth day; -prescribing, to the subject, a medication for a twenty-one-day unsupervised mode if -the urine toxicological screen in the fourteen-day unsupervised mode is negative; or -the medication adherence is concluded in the subject, wherein the medication adherence is concluded if a variance between the medication concentration in the blood sample of the subject from laboratory testing on the fourteenth day and the medication concentration obtained from the point-of-care device estimated on the fourteenth day is equal to or less than 20%, wherein during the twenty-one-day unsupervised mode, the method comprises requiring the subject to take the urine toxicological screen and the venous blood sample laboratory testing randomly; and -prescribing, to the subject, a medication for a twenty-eight-day unsupervised mode if the urine toxicological screen in the twenty-one-day unsupervised mode is negative, wherein on a twenty-eighth day of the twenty-eight-day unsupervised mode, the method comprises collecting the venous blood sample from the subject for laboratory testing of the medication concentration in the blood sample of the subject and comparing it with the medication concentration obtained from the point-of-care device estimated on the twenty-eighth day.

In this regard, for the first 5 days of outpatient medication, for example buprenorphine (BUP) maintenance treatment, the subject attends the clinic daily for in-person supervised dosing and to take a UDS test at each visit or a minimum of 3 out of 5 visits. Upon adherence (i.e. all doses taken; at least three negative UDS; all UDS positive for the medication, the subject receives a 7-day medication take-home doses and asked to return to the clinic 1 week later. Upon successful return to the clinic reporting taking medications as prescribed and providing a negative opioid urinary screen (and positive for the medication), the subject is given a 14-day medication take-home doses and are counselled not to take the medication on the day they return to the clinic. Fourteen days later, the subject returning to the clinic is observed collection of a venous blood sample that are send to the laboratory for medication quantitation. At this visit, the subject is provided a 14-day supply (with same directions) and asked to return to the clinic 2 weeks later. On return to the clinic, the procedure is repeated, and medication concentration reported by the laboratory from the previous visit are contrasted with the medication concentration predicted using the pharmacokinetic model (estimated from the previous visit). Medication adherence is concluded if the variance between the reported and predicted medication concentrations fall within 20%. The subject who is considered medication adherence and provides an opioid free Urinary Drug Screens are provided a 21-days (3 weeks) medication take-home dose. During this 21-days supply the subject may be randomly asked to attend for UDS and blood testing. On successful return to the clinic after 21 days, the patients with evidence of continued abstinence, are provided a 28-days medication take-home dose supply and asked to return I month later and the procedures are repeated.

In an embodiment, the method comprises returning the subject to a previous unsupervised duration, if the medication adherence or opioid abstinence is not concluded in the subject. The subjects not adhering to the above-mentioned procedure at the outset or for the requirements of the 7-days take-home dose, are held at a 5-day supervised dosing requirement pending evidence of adherence and abstinence. The subjects receiving 14-days take-home dose who were non-adherent or non-abstinent were 'reset' to receive a 7-day take-home dose. The subjects receiving a 2 I -day and 28-day take-home dose who were non-adherent or non-abstinent were reset to a 14-day or 2I-day take-home dose, respectively.

In an embodiment, the method comprises returning the subject to a 5-day observed treatment, if both the medication adherence or opioid abstinence are not concluded in the subject. At any point, a non-adherent and non-abstinent subject is held in a 5-day supervised dosing and UDS testing 15 regime.

In an embodiment, the method comprises altering at least one of: a type of the medication, a therapy for the subject, if the medication adherence is different from the predefined threshold.

In an embodiment, the method comprises following a comprehensive medication management manual. Notably, the comprehensive medication treatment manual includes detailed clinical 20 procedures and patient counseling framework.

The present disclosure also relates to an algorithm for allocation a subject to a treatment based on response prediction using a medication elimination rate constant. The subject is stabilized on a medication treatment (comprising such as a buprenorphine/naloxone (BUP/NX) concentration) and then the medication (BUP/NX) elimination rate constant is calculated and body mass index (BMI) of the subject is recorded. Additionally, baseline impulsiveness, AST depression family needs and motivation of the subject to be involved with the treatment is performed and recorded. A prediction equation is applied based on the calculated medication elimination rate constant and body mass index (BM° of the subject.

In this regard, if the prediction equation shows the subject to be less than 75% opioid negative UDS, then the medication treatment (comprising such as a buprenorphine/naloxone (BURNX) concentration) is either tapered or an alternate treatment is prescribed for the subject. In such cases, for example, the alternate treatment may comprise adding a new medication treatment (for example Naltrexone) to the existing one (BUR/NX concentration).

However, if the prediction equation shows the subject to be more than 75% opioid negative UDS, then the treatment comprises assessing family involvement in the treatment process. If the family involvement is low, then the treatment process is directed at increasing family involvement by extended family therapy and family orientation in the treatment process. If the family involvement is high, then a cognitive assessment is performed for the subject. If no cognitive impairment is observed the subject is continued to be treated and monitored for history of pregabalin. If there is no history of pregabalin, the subject is discharged to an out-patient group and continued on the prescribed treatment process (such as BURNX concentration) in an out-patient mode. However, if after performing the cognitive assessment, there is cognitive impairment in the subject or if there is history of pregabalin, the subject is referred to a clinical psychology treatment group and the CBT thereon is started. Upon successful clinical psychology treatment, the subject is continued on the prescribed treatment process (such as BURNX concentration) in an out-patient mode.

The present disclosure also relates to the computer program product as described above. Various embodiments and variants disclosed above apply mutatis mutandis to the computer program 20 product.

The computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a processor to execute the aforementioned method.

Optionally, the computer program product is implemented as an algorithm, embedded in a software stored in the non-transitory machine-readable data storage medium. The non-transitory machine-readable data storage medium may include, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. Examples of implementation of the computer-readable medium include, but are not limited to, Electrically Erasable Programmable Read-Only Memory (EEPROM), Random Access Memory (RAM), Read Only Memory (ROM), Hard Disk Drive (HDD), Flash memory, a Secure Digital (SD) card, Solid-State Drive (SSD), a computer readable storage medium, and/or CPU cache memory.

Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims.

Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural.

DETAILED DESCRIPTION OF THE DRAWINGS

Referring to FIG. 1, illustrated is a schematic illustration of a point-of-care device 100 for monitoring a medication adherence in a subject, in accordance with an embodiment of the invention. The point-of-care device 100 comprises a light source 102 for emitting a light; a first filter 104 for receiving the light emitted by the light source 102 and filtering the light at a specific excitation wavelength. Moreover, the point-of-care device 100 comprises a beam splitter 106 configured to split a beam of light into two beams, wherein a first beam from amongst the two beams is received by a first photomultiplier tube 108 configured to detect the specific excitation wavelength of the first beam, and a second beam from amongst the two beams is received by a sample cuvette 110. Furthermore, the point-of-care device 100 comprises a second filter 112 for receiving the light emitted by the sample cuvette 110 and filtering the light at a specific emission wavelength; a second photomultiplier tube 114 configured to detect the specific emission wavelength of the light; and a detector 116 for detecting a medication concentration in blood sample of the subject based on the detected specific emission wavelength of the light. Moreover, the point-of-care device 100 further comprises a database 118 to store a data, wherein the data comprises: a medication concentration, an estimated elimination rate of the medication, a subject detail.

FIG. 1 is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

Referring to FIG. 2, illustrated is a schematic illustration of a system 200 for delivering incentivized medication adherence and opioid abstinence in a subject, in accordance with an embodiment of the invention. The system 200 comprises a point-of-care device 202 (such as the point-of-care device 100 of FIG. I) and a pharmacokinetic model 204, associated with the point-of-care device 202, configured to receive a data from the point-of-care device 202 and assess medication adherence based on the data received from the point-of-care device 202.

FIG. 2 is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

Referring to FIG. 3, illustrated is a flowchart 300 illustrating steps of a method for delivering incentivized medication adherence and opioid abstinence in a subject, in accordance with an embodiment of the invention. At step 302, the subject is stabilized on a medication concentration. At step 304, data from the subject is obtained using a point-of-care device (such as the point-ofcare device 100 of FIG. 1 or the point-of-care device 202 of FIG. 1). At step 306, the medication take-home doses of the subject is altered based on the data obtained, wherein the data obtained is associated with the medication adherence that is different from a predefined threshold.

The steps 302, 304, and 306 are only illustrative and other alternatives can also be provided where one or more steps are added, one or more steps are removed, or one or more steps are provided in a different sequence without departing from the scope of the claims herein.

Referring to FIG. 4, illustrated is a flowchart 400 illustrating an algorithm for allocation a subject to a treatment based on response prediction using a medication elimination rate constant, in accordance with an embodiment of the invention. As shown, the subject is stabilized on a medication treatment (comprising such as a buprenorphine/naloxone (BUR/NIX) concentration) and then the medication (BURINX) elimination rate constant is calculated and body mass index (BMI) of the subject is recorded. Additionally, baseline impulsiveness, ASI depression family needs and motivation of the subject to be involved with the treatment is performed and recorded. A prediction equation is applied based on the calculated medication elimination rate constant and body mass index (BMI) of the subject.

FIG. 4 is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

Referring to FIG. 5, illustrated is an exemplary reference calibration curve of a variation of a concentration of known samples with respect to a response of the detector, in accordance with an embodiment of the invention. In the reference calibration curve, a concentration of known samples is represented along a horizontal axis and the response is represented along a vertical axis. The response and the concentration of the known samples are plotted along a line. Herein, the medication concentration in the blood sample can be obtained by plotting points on the line and intercept on the horizontal axis.

FIG. 5 is merely an example, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

Claims

CLAIMS1. A point-of-care device (100, 202) for monitoring a medication adherence in a subject, the pointof-care device comprising: -a light source (102) for emitting a light; -a first filter (104) for receiving the light emitted by the light source and filtering the light at a specific excitation wavelength; -a beam splitter (106) configured to split a beam of light into two beams, wherein -a first beam from amongst the two beams is received by a first photomultiplie (108) tube configured to detect the specific excitation wavelength of the first beam, and -a second beam from amongst the two beams is received by a sample cuvette (110); -a second filter (112) for receiving the light emitted by the sample cuvette and filtering the light at a specific emission wavelength; -a second photomultiplier tube (114) configured to detect the specific emission wavelength of the light: and -a detector (116) for detecting a medication concentration in blood sample of the subject based on the detected specific emission wavelength of the light.
2. A point-of-care device of claim 1, wherein the medication adherence in the subject is associated with a measurement of a concentration of the medication in a blood sample from the subject.
3. A point-of-care device of claim 1 or 2, wherein the medication is an opioid agonist selected from at least one of: a buprenorphine, a methadone, or an opioid agonist such as a naltrexone, a nalox one.
4. A point-of-care device of claim 1, 2 or 3, wherein the blood sample is a venous blood sample or a capillary blood sample.
5. A point-of-care device of any of the preceding claims, further comprising a database (118) to store a data, wherein the data comprises: a medication concentration, an estimated elimination rate of the medication, a subject detail.
6. A system (200) for delivering incentivized medication adherence and opioid abstinence in a subject, the system comprising: - a point-of-care device of any of claims 1-5; and - a pharmacokinetic model (204), associated with the point-of-care device (100, 202), configured to -receive a data from the point-of-care device; and -assess medication adherence based on the data received from the point-of-care device.
7. A system of claim 6, wherein the data received from the point-of-care device (100, 202) comprises: a medication concentration, an estimated elimination rate of the medication, a subject detail.
8. A system of claim 6 or 7, wherein the pharmacokinetic model (204) is further configured to predict a likelihood of response to the medication.
9. A system of claim 6, 7 or 8, wherein the pharmacokinetic model (204) is further configured to generate a predictive model to predict a personalized treatment for the subject.
10. A system of any of claims 6-9, wherein the personalized treatment for a given subject is associated with a reduction in illicit opioid use in the given subject.
11. A system of any of claims 6-10, wherein the pharmacokinetic model (204) is further configured to create a calibration curve between a medication concentration obtained from laboratory testing and a medication concentration obtained from the point-of-care device (100, 202), to assess medication adherence.
12. A method for delivering incentivized medication adherence and opioid abstinence in a subject, 20 the method comprising: -stabilizing the subject on a medication concentration; -obtaining data from the subject using a point-of-care device of any of claims 1-5; and -altering the medication take-home doses of the subject based on the data obtained, wherein the data obtained is associated with the medication adherence that is different from a predefined 25 threshold.
13. A method of claim 12, wherein the method is selected from a non-supervised mode or a sem supervised mode.
14. A method of claim 12 or 13, further configured to predict a likelihood of response to the medication.
15. A method of claim 12, 13 or 14, further configured to predict a personalized treatment for the subject.
16. A method of any of claims 12-15, wherein the method comprises prescribing medication for a period of 7 to 28 days in the non-supervised mode or the semi-supervised mode.
17. A method of any of claims 12-16, wherein the method comprises -maintaining the subject on a medication in a five-day outpatient mode, wherein the five-day outpatient mode comprises supervised dosing and/or at least three urine toxicological screen; -prescribing, to the subject, a medication for a seven-thy unsupervised mode if the urine toxicological screen in the five-day outpatient mode is negative, wherein the seven-day unsupervised comprises supervised dosing and/or at least three urine toxicological screen; -prescribing, to the subject, a medication for a fourteen-day unsupervised mode if the urine toxicological screen in the seven-day unsupervised mode is negative, wherein on a fourteenth day of the fourteen-day unsupervised mode, the method comprises (a) requiring the subject not to take the medication on a test day; (b) collecting a venous blood sample from the subject for laboratory testing of the medication concentration in the blood sample of the subject; (c) prescribing, to the subject, a medication for another fourteen-day unsupervised mode; and (d) repeating steps (a) to (b) and comparing the medication concentration in the blood sample of the subject from laboratory testing on the fourteenth day with the medication concentration obtained from the point-of-care device estimated on the fourteenth day; -prescribing, to the subject, a medication for a twenty-one-day unsupervised mode if -the urine toxicological screen in the fourteen-day unsupervised mode is negative; or -the medication adherence is concluded in the subject, wherein the medication adherence is concluded if a variance between the medication concentration in the blood sample of the subject from laboratory testing on the fourteenth day and the medication concentration obtained from the point-of-care device estimated on the fourteenth day is equal to or less than 20%, wherein during the twenty-one-day unsupervised mode, the method comprises requiring the subject to take the urine toxicological screen and the venous blood sample laboratory testing randomly; and -prescribing, to the subject, a medication for a twenty-eight-day unsupervised mode if the urine toxicological screen in the twenty-one-day unsupervised mode is negative, wherein on a twenty-eighth day of the twenty-eight-day unsupervised mode, the method comprises collecting the venous blood sample from the subject for laboratory testing of the medication concentration in the blood sample of the subject and comparing it with the medication concentration obtained from the point-of-care device estimated on the twenty-eighth day.
18. A method of any of claims I 2-I 7, wherein the method comprises returning the subject to a previous unsupervised duration, if the medication adherence or opioid abstinence is not concluded in the subject.
19. A method of any of claims 12-18, wherein the method comprises returning the subject to a 5-day observed treatment, if both the medication adherence or opioid abstinence are not concluded in the subject.
20. A method of any of claims 12-19, wherein the method comprises altering at least one of: a type of the medication, a therapy for the subject, if the medication adherence is different from the predefined threshold.