WO2022216244A1 - A pharmaceutical product identification method and a system operating based on the said method - Google Patents

A pharmaceutical product identification method and a system operating based on the said method Download PDF

Info

Publication number
WO2022216244A1
WO2022216244A1 PCT/TR2021/050337 TR2021050337W WO2022216244A1 WO 2022216244 A1 WO2022216244 A1 WO 2022216244A1 TR 2021050337 W TR2021050337 W TR 2021050337W WO 2022216244 A1 WO2022216244 A1 WO 2022216244A1
Authority
WO
WIPO (PCT)
Prior art keywords
sample
family
drug
library
control unit
Prior art date
Application number
PCT/TR2021/050337
Other languages
French (fr)
Inventor
Derya CEBECİ
Rafet MALTAŞ
Original Assignee
Portmera Araştirma Li̇mi̇ted Şi̇rketi̇
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Portmera Araştirma Li̇mi̇ted Şi̇rketi̇ filed Critical Portmera Araştirma Li̇mi̇ted Şi̇rketi̇
Priority to PCT/TR2021/050337 priority Critical patent/WO2022216244A1/en
Publication of WO2022216244A1 publication Critical patent/WO2022216244A1/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/15—Medicinal preparations ; Physical properties thereof, e.g. dissolubility
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/9508—Capsules; Tablets
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/018—Certifying business or products
    • G06Q30/0185—Product, service or business identity fraud
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H70/00—ICT specially adapted for the handling or processing of medical references
    • G16H70/40—ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage

Definitions

  • the invention relates to a fast, precise and practical pharmaceutical product identification method developed to identify the drug on-site and a system operating based on the said method.
  • the counterfeit drug trade is a growing global public health and also an economic and social problem. ‘According to estimates of the World Health Organization (WHO) in 2018, 10 percent of the drugs in underdeveloped and developing country markets are counterfeit or substandard. This percentage can rise up to 70 percent in some regions such as Africa. Still, ‘According to the United Nations Office on Drugs and Crime (UNODC) report in 2020, it is estimated that the market for the counterfeit and substandard drugs is between 65 and 200 billion dollars annually.’ According to estimates, more than one million people die each year from counterfeit drugs. All these show that drug counterfeiting is very common and there is a need for global approach to combat counterfeit drugs. In this context, analyzing the drug on-site, determining its authenticity at real-time, and sharing the data globally will make this combat more effective and efficient.
  • WHO World Health Organization
  • UODC United Nations Office on Drugs and Crime
  • spectroscopy-based recognition systems the spectrum of an unknown material is is compared individually with the spectra of known materials in the library.
  • the possibility of correct match decreases and the precision of selectivity decreases. Selectivity is compromised as the library is expanded.
  • the sample is not as stated on the label, it does not actually show the real identity of the unknown drug.
  • the sample is identified as counterfeit and contains an active ingredient other than the active ingredient indicated on the label, it does not provide information about this different active ingredient.
  • the active ingredient identity of the unknown drug cannot be determined in current technologies as they are set in verification mode and as the active ingredient family or the therapeutic supergroup the medicines belong to is not predefined in the spectral database. Therefore, in these regards these techniques are limited.
  • Spectroscopic technologies are usually not widely used in analysis due to their high price.
  • most of the spectroscopic analysis techniques used in the state of the art used a very wide spectral range ( ⁇ 800-2400 nm) or a very wide range above 1500 nm.
  • the near infrared regions (NIR) below 1000 nm, particularly the 900-1700 nm region have not been investigated since they have much less information and are less specific for the purpose compared to the region above 1600 nm or the region between 800-2500 nm.
  • NIR near infrared regions
  • prior technical research has been done in such that wider wavelength regions are required to provide sufficient data to create selective models.
  • the specific region of 900-1700 nm has not been used in any research and drug identification using this region has not been carried out before.
  • the aim of the invention is to achieve a fast, precise and practical pharmaceutical finished product identification method developed to identify the drug on-site and a system operating based on the said method.
  • counterfeit drugs are quickly determined on-site without using any chemicals.
  • more products can be scanned on-site and fewer samples can be transferred to laboratories for more analysis.
  • the decision-making process of the legal authorities is accelerated.
  • it can be ensured that in the global combat against counterfeiting, products analyzed in different regions but found to have the same chemical fingerprint will be matched (for example, the same chemical signal is received in the measurements made in Nigeria and France) and that authorities will work in a more harmonized way on the possibility of these products coming from the same supplier.
  • the method of the invention is a spectroscopic method that determines a drug family or active pharmaceutical ingredient (API) without using any chemicals and without the need for active pharmaceutical ingredient as reference.
  • the method identifies drug families in a large drug database (more than 500 or unlimited) without using any chemicals and without destroying them.
  • the unique product sample to be tested does not have to be included in the library to identify family thereof, as long as there is sufficient number of samples belonging to the same drug family in the library.
  • the bucket approach if there is a sufficient variety of samples in therapeutic supergroup (or therapeutic bucket) of API, an unknown sample not found in the library but belong to a therapeutic supergroup represented by multiple medicines in the library can be identified with more than 90% accuracy.
  • the API family of an unknown medicine can be determined by using the NIR spectral fingerprint.
  • An "easy-to-use group classifier” method has been developed to identify the drug product family (or active pharmaceutical ingredients (APIs)) without using any consumables and without destroying the products.
  • the method is a "one-step” method; that is, instead of selecting a specific wavelength range for a specific drug to optimize precision, it places all drugs from the same family into a single group (or bucket), regardless of whether they have same, similar or completely different formulations.
  • the method can then determine drug families with more than 90% accuracy by making measurements within the NIR region for all samples.
  • apparatus contained in the system of the invention is portable, light-weight, economical and precise. It contains a universal identification database containing comprehensive information on the chemical composition of more than 500 drugs. Also new drugs and products can be added to the database.
  • the method of the invention provides a fast and non-destructive analysis method in order to control the pharmaceutical products imported to countries at customs checkpoints. Thus, analysis processes that take hours or even days can be performed in seconds since the products do not need to be sent to the laboratory.
  • the apparatus of the invention is also used in the quality control of strategic drugs and drugs for epidemics stocked by the states.
  • the system using Internet of Things (IOT) technology can determine counterfeit and non-standard drugs in 20 seconds.
  • IOT Internet of Things
  • the method of the invention allows to identify the medicine’s API family in a single step by placing all drugs coming from the same family, but being same, similar or completely different formulations, into a single group (or bucket).
  • the identity of the drug whose identity is checked is determined with high accuracy since there are quite a number of drugs or therapeutic supergroup it belongs is predefined in the library using the technique.
  • the invention has a large spectral data library.
  • APIs raw materials
  • the spectrum in the library can be increased as much as desired without decreasing the selectivity precision. As the number of the products in the library increases, the accuracy rate increases.
  • the method of the invention and the apparatus operating based on the said method are simpler and easier than the state of the art. Furthermore, with the apparatus of the invention, identification in the wavelength range of 900-1700 nm can also be made.
  • Figure 1 Representative view of the system of the invention.
  • Figure 2. View of the flow diagram of the system of the invention.
  • the system (10) of the invention includes an apparatus (1) and a main server (2), to determine whether pharmaceutical finished products are counterfeit or not by analyzing which drug family (or active ingredient or drug substance) they belong to.
  • the server (2) comprises at least one control unit (2.1), at least one wireless communication unit (2.3) enabling communication with an apparatus (1), and at least one data storage unit
  • the apparatus (1) comprises at least one light source (1.1) transmitting light at the predetermined near infrared wavelengths to the sample (N), at least one sensor (1.2) sensing the light reflected or transferred from the sample (N), at least one reservoir
  • the system (10) of the invention includes at least one control unit (2.1), after optical scanning of the sample (N) positioned in an apparatus (1), controlling whether the sample (N) belongs to a predefined therapeutic family (or group) in the library in a data storage unit (2.2) by receiving the data after the data (i.e., received chemical fingerprint signal) received from the sensor (1 .2) which senses the NIR signal from said sample is transmitted to the main server (2) by means of a communication unit, determining the unidentified sample (N) family, i.e., identifying (or verifying the identified sample family) by determining the group with the highest match by correlation (matching) with all drugs in all groups registered in the data storage unit (2.2), and transmitting the data to the communication unit (1.4) included in the apparatus (1) via another communication unit (2.3) by not confirming if it is not a sample (N) belonging that family following the said control and enabling the said data to be displayed on the display (1.5) and on the other hand, confirming this if it belongs to the family and performing the transmit
  • Control unit (2.1) correlates (matches) each unknown drug with all groups registered in the data storage unit (2.2). This correlation can be done with the entire spectrum that includes the entire energy range from the sample, or can be done in a certain energy range specific to each group determined as the optimum range for that group. If the group contains only one drug product, rays in all wavelengths (in all energies) coming from the sample are used for correlation match. If the group contains more than one product, a correlation match is done in the optimum range specific to that group for each group predetermined by univariate or multivariate analysis. This optimum range can be a narrow wavelength (energy) range or can be in the range that includes the entire NIR region. Then, after the matching, the unknown sample (N) family is determined by the control unit (2.1) by determining the group with the highest match following the protocol represented in Figure 2 or if known, it is verified with the label.
  • a portable spectroscopy apparatus (1) operating in reflection mode has been developed.
  • the apparatus (1) included in the system of the invention can operate in the entire NIR range (800-2500 nm) and in all resolutions.
  • a device (1) operating in the narrow wavelength range of 900 to 1700 nm has been developed.
  • a much more cost-efficient, adoptable and scalable (or portable) apparatus (1) is provided in the invention with the apparatus (1) used in the preferred embodiment of the invention than those existing in the state of the art.
  • the drug family determination algorithm and the drug family verification algorithm developed with the apparatus (1) complying with these criteria gives a 90% accuracy and a 95% accuracy, respectively. Better results can be obtained in a wider wavelength range and at high resolution.
  • Sample (N) is a pharmaceutical finished product in the preferred embodiment of the invention, although it varies according to the sectors.
  • the sample (N) is a pharmaceutical composition or any component of the pharmaceutical composition, such as active ingredient and/or excipient thereof.
  • the apparatus (1) included in the system (10) of the invention determines whether the pharmaceutical end products are counterfeit or not, it is not limited to this in practice.
  • it is determined which group of the NIR spectra registered in the library the pharmaceutical end product family (i.e., active ingredients thereof) belongs (or approximately belongs) to, which is obtained by sensing the ray reflecting (or scattering) from the sample (N) only by sending lights at certain wavelengths in the near infrared region to the sample (N) without using any consumables, and the sample (N) identity is determined accordingly. Therefore, the said analysis is carried out by a method (100) and the system (10) of the invention is operated with the said method (100).
  • the sample (N) analyzed intact and/or the sample (N) is not broken in order to receive signal from the sample (N) placed in the apparatus (1) of the invention and to reach the core of the sample (N) and therefore, the sample (N) identity is determined by determining the active ingredient class (or group).
  • the method (100) of the invention has sufficient precision such that it carries out analysis over coatings of drug tablet products and over shells of capsule products and analyzes the drug substances within the capsules under the tablet coating.
  • the vibrational spectra in all embodiments of this invention are determined by the near infrared (NIR) spectroscopy technique and thereby it is ensured that pharmaceutical end products can be determined (identified) rapidly and/or verified by assessing the substantial and/or extensive chemical fingerprints of the said samples (N).
  • This invention also determines the source or origin of counterfeit pharmaceuticals by following and comparing the chemical fingerprints.
  • the method (100) of the invention operates according to the following method steps in order to analyze whether the drug is counterfeit or not by determining the chemical fingerprints of pharmaceutical substances:
  • step (a) If the match result after step (a) is the same with the product specified on the label, the product passes the test
  • step (a) If the match result after step (a) is not the same with the product specified on the label, the product fails the test and is transferred to the laboratory as a suspected product
  • Drug having the brand name Lipitor is a drug from the "atorvastatin" family.
  • the Lipitor spectrum to be tested is compared with the spectra of the products in the database.
  • the sample (N) fails the test in two cases. First, if the highest similarity index calculated for the Lipitor sample tested is below 95% or secondly, if the similarity index is above the threshold (i.e.> 95%) but the sample (N) is not identified belonging to the "atorvastatin” therapeutic supergroup then the sample (N) is considered suspected as well and is sent to the laboratory for further testing.
  • the evaluation proceeds as follows:
  • the lowest similarity index is at a predetermined value, for example at least 70% (only one threshold value being 70% is sufficient). All products below this threshold value are reported as unidentified. That is, the system reports that these products are unidentified).
  • the similarity index value is a predetermined value for example 70% or a higher value, looking at the similarity (correlation) index obtained from the first three matches and/or the ratio of similarity index rates to each other (lower value/higher value)
  • the method (100) of the invention in a narrow region (900-1700 nm) where less spectral information is available, identifies the product family with more than 90% accuracy and verify it with more than 95% accuracy using the grouping approach.
  • Grouping approach is the initial grouping by placing as many different formulations as possible from the same drug substance family in the same therapeutic supergroup (i.e., the same API bucket).
  • the invention is a very simple and one-step model compared to the prior arts. It should be understood that by a one-step model is meant each new product is placed directly to their therapeutic supergroup (or buckets or groups). If the sample (N) is a product whose family does not exist in the library, then a new bucket or group is added. Each new drug is added to its supergroup in a single and large database, and the identity of the drug family is determined by running a correlation algorithm. Therefore, each drug is added to its supergroup in the data storage unit (2.2) included in the main server (2). Accordingly, each unknown drug is correlated (matched) with all drugs in all groups by the control unit (2.1). Then, the unidentified sample (N) family is determined by the control unit (2.1) by determining the group with the highest match obtained from the match.
  • the said algorithm identifies and/or verifies the active ingredient of a drug without any prior knowledge of the drug.
  • Exemplary pharmaceutical product groups (or buckets) for some drug substances are given below:
  • the method (100) of the invention and the system (10) operating based on the said method (100) have industrial applicability, especially for use in identifying the drugs in the pharmaceutical field.
  • the invention is not limited to the exemplary embodiments above, and a person skilled in the art can easily put forth other different embodiments of the invention. These should be considered within the scope of protection of the invention claimed by the claims.

Landscapes

  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • Immunology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Strategic Management (AREA)
  • Primary Health Care (AREA)
  • Tourism & Hospitality (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Medicinal Chemistry (AREA)
  • General Business, Economics & Management (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Theoretical Computer Science (AREA)
  • Pharmacology & Pharmacy (AREA)
  • Accounting & Taxation (AREA)
  • Molecular Biology (AREA)
  • Food Science & Technology (AREA)
  • Finance (AREA)
  • Development Economics (AREA)
  • Human Resources & Organizations (AREA)
  • Biophysics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Epidemiology (AREA)
  • Toxicology (AREA)
  • Child & Adolescent Psychology (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

The invention relates to a system (1) comprising the following, and a method (100) enable the said system (10) to operate, - a server (2) comprising at least one wireless communication unit (2.3) and at least one data storage unit (2.2) and at least one apparatus (1) comprising at least one light source (1.1), at least one sensor (1.2), at least one reservoir (1.3), at least one wireless communication unit (1.4) and at least one display (1.5) and at least one control unit (2.1), after optical scanning of the sample (N) positioned in the apparatus (1), controlling whether the sample (N) belongs to a predefined therapeutic family in the library in a data storage unit (2.2) by receiving the data after the data received from the sensor (1.2) which senses the NIR signal from sample (N) is transmitted to the main server (2) by means of a communication unit, identifying the unidentified sample (N) by determining the group with the highest match by correlation with all drugs in all groups registered in the data storage unit (2.2), and transmitting the data to the communication unit (1.4) included in the apparatus (1) via another communication unit (2.3) by not confirming if it is not a sample (N) belonging that family following the said control and enabling the said data to be displayed on the display (1.5) and on the other hand, confirming this if it belongs to the family and performing the transmitting similarly to the apparatus (1) and enabling this to be displayed on the display (1.5) and therefore as a result of the said controls providing the confirmation whether the sample (N) is counterfeit or not.

Description

A PHARMACEUTICAL PRODUCT IDENTIFICATION METHOD AND A SYSTEM OPERATING BASED ON THE SAID METHOD Technical Field
The invention relates to a fast, precise and practical pharmaceutical product identification method developed to identify the drug on-site and a system operating based on the said method.
Prior Art
The counterfeit drug trade is a growing global public health and also an economic and social problem. ‘According to estimates of the World Health Organization (WHO) in 2018, 10 percent of the drugs in underdeveloped and developing country markets are counterfeit or substandard. This percentage can rise up to 70 percent in some regions such as Africa. Still, ‘According to the United Nations Office on Drugs and Crime (UNODC) report in 2020, it is estimated that the market for the counterfeit and substandard drugs is between 65 and 200 billion dollars annually.’ According to estimates, more than one million people die each year from counterfeit drugs. All these show that drug counterfeiting is very common and there is a need for global approach to combat counterfeit drugs. In this context, analyzing the drug on-site, determining its authenticity at real-time, and sharing the data globally will make this combat more effective and efficient.
In spectroscopy-based recognition systems, the spectrum of an unknown material is is compared individually with the spectra of known materials in the library. In such systems, as the number of spectra in the library increases, the possibility of correct match decreases and the precision of selectivity decreases. Selectivity is compromised as the library is expanded.
Some countries use portable scanning technologies to screen counterfeit drugs on-site. Thus, fewer samples are transferred to central laboratories to undergo costly and time- consuming verification analysis, and also the decision-making process is accelerated for executing legal action on-site. However, existing technologies cannot be easily scaled for global adaptation and also cannot meet technological requirements. More specifically, current technologies operate in verification mode and authenticate samples by verifying already known (or existing or predefined) drug label information. If the label does not match the analysis results or does not exceed a certain threshold value, the sample is considered counterfeit and sent to laboratories for detailed examination. One very important limitation of this approach is that if the sample analyzed is not available in the database of the system, validation analysis of that sample cannot be performed. Secondly, if the sample is not as stated on the label, it does not actually show the real identity of the unknown drug. In other words, if the sample is identified as counterfeit and contains an active ingredient other than the active ingredient indicated on the label, it does not provide information about this different active ingredient. In fact, the active ingredient identity of the unknown drug cannot be determined in current technologies as they are set in verification mode and as the active ingredient family or the therapeutic supergroup the medicines belong to is not predefined in the spectral database. Therefore, in these regards these techniques are limited.
Technologies used in the state of the art further perform wet chemical techniques to identify the drug family or use a very limited spectral data library that applies only for samples in their library. For example, The GPHF-Minilab company developed a similar platform for verification only. In other words, they developed a technique that verifies a known drug. On the other hand, the study of TellSpec company consists of only the algorithm they developed for food analytics.
A rapid pharmaceutical identification and verification system is mentioned in the patent document numbered US 7218395 B2 falls into the state of the art. This system is based on Raman spectroscopy technique.
In another document, “Degardin, K.; Guillemain, A.; Guerreiro, N. V.; Roggo, Y., Near infrared spectroscopy for counterfeit detection using a large database of pharmaceutical tablets. Journal of Pharmaceutical and Biomedical Analysis 2016, 128, 89-97. “, a system which determines whether pharmaceutical tablets are counterfeit or not by using near infrared (NIR) Spectroscopy is mentioned. In the method developed for each new product added, the models used must be updated. In addition, the algorithms used in the document are time consuming and complex. Further, in this study, analyzes were performed using a very wide range of NIR wavelengths (i.e., 1000-2500 nm). Thus, the sensor systems used are more costly systems.
Spectroscopic technologies are usually not widely used in analysis due to their high price. However, as mentioned above, most of the spectroscopic analysis techniques used in the state of the art used a very wide spectral range (~ 800-2400 nm) or a very wide range above 1500 nm. In the prior art, the near infrared regions (NIR) below 1000 nm, particularly the 900-1700 nm region have not been investigated since they have much less information and are less specific for the purpose compared to the region above 1600 nm or the region between 800-2500 nm. Generally, prior technical research has been done in such that wider wavelength regions are required to provide sufficient data to create selective models. The specific region of 900-1700 nm has not been used in any research and drug identification using this region has not been carried out before.
There is no prior art used to identify the drug product family among hundreds of samples in seconds in a one-step method with a low error rate and without destroying the sample. The methods used in the prior art are not one-step methods that are very complex and either create a separate model for each specific drug family or cover multiple sub-models.
Therefore, it is necessary to develop a system that minimizes or eliminates the aforementioned disadvantages in the state of the art.
Summary of the Invention:
The aim of the invention is to achieve a fast, precise and practical pharmaceutical finished product identification method developed to identify the drug on-site and a system operating based on the said method.
With the method and system of the invention, counterfeit drugs are quickly determined on-site without using any chemicals. Thus, more products can be scanned on-site and fewer samples can be transferred to laboratories for more analysis. By doing so, the decision-making process of the legal authorities is accelerated. Furthermore, it can be ensured that in the global combat against counterfeiting, products analyzed in different regions but found to have the same chemical fingerprint will be matched (for example, the same chemical signal is received in the measurements made in Nigeria and France) and that authorities will work in a more harmonized way on the possibility of these products coming from the same supplier.
The method of the invention is a spectroscopic method that determines a drug family or active pharmaceutical ingredient (API) without using any chemicals and without the need for active pharmaceutical ingredient as reference. The method identifies drug families in a large drug database (more than 500 or unlimited) without using any chemicals and without destroying them. With the invention, the unique product sample to be tested does not have to be included in the library to identify family thereof, as long as there is sufficient number of samples belonging to the same drug family in the library. With the bucket approach, if there is a sufficient variety of samples in therapeutic supergroup (or therapeutic bucket) of API, an unknown sample not found in the library but belong to a therapeutic supergroup represented by multiple medicines in the library can be identified with more than 90% accuracy. As long as there is enough sampling in a certain API bucket, with the developed method the API family of an unknown medicine can be determined by using the NIR spectral fingerprint.
An "easy-to-use group classifier" method has been developed to identify the drug product family (or active pharmaceutical ingredients (APIs)) without using any consumables and without destroying the products. The method is a "one-step" method; that is, instead of selecting a specific wavelength range for a specific drug to optimize precision, it places all drugs from the same family into a single group (or bucket), regardless of whether they have same, similar or completely different formulations. The method can then determine drug families with more than 90% accuracy by making measurements within the NIR region for all samples.
Therefore, apparatus contained in the system of the invention is portable, light-weight, economical and precise. It contains a universal identification database containing comprehensive information on the chemical composition of more than 500 drugs. Also new drugs and products can be added to the database.
With this apparatus, it is determined whether a drug is counterfeit or not by on-site and non-destructive measurement within seconds without any chemical or physical treatment. One can obtain information with high accuracy even from weak signals with the unique artificial intelligence technology that can recognize, distinguish and classify with high precision. Apparatus does not require any chemical treatment or qualified personnel to do so.
The method of the invention provides a fast and non-destructive analysis method in order to control the pharmaceutical products imported to countries at customs checkpoints. Thus, analysis processes that take hours or even days can be performed in seconds since the products do not need to be sent to the laboratory. The apparatus of the invention is also used in the quality control of strategic drugs and drugs for epidemics stocked by the states. The system using Internet of Things (IOT) technology can determine counterfeit and non-standard drugs in 20 seconds. Currently, more than 500 drugs can be recognized and analyzed with 90% accuracy with the method and apparatus operating based on the said method.
The method of the invention allows to identify the medicine’s API family in a single step by placing all drugs coming from the same family, but being same, similar or completely different formulations, into a single group (or bucket). In fact, the identity of the drug whose identity is checked is determined with high accuracy since there are quite a number of drugs or therapeutic supergroup it belongs is predefined in the library using the technique. The invention has a large spectral data library.
The method of the invention has the following advantages:
-It does not require raw materials (APIs) to define the product’s API family
-It takes less time and requires less effort to create the method
-Accuracy of the method increases as more samples are added to the product library.
Thus, with the invention;
1.An unknown drug is measured,
2. Spectrum of the unknown drug is compared with all drug groups in the library by using the method and therefore, the therapeutic product family (active ingredient group) is easily determined.
3. Parameters above a set threshold value are estimated. In the apparatus of the invention, the spectrum in the library can be increased as much as desired without decreasing the selectivity precision. As the number of the products in the library increases, the accuracy rate increases.
The method of the invention and the apparatus operating based on the said method, are simpler and easier than the state of the art. Furthermore, with the apparatus of the invention, identification in the wavelength range of 900-1700 nm can also be made.
Description of the Drawings
Figure 1. Representative view of the system of the invention. Figure 2. View of the flow diagram of the system of the invention.
Explanation of References in the Drawings
Numbers in the drawings are given below in order to provide a further understanding of the invention.
10. System
1. Apparatus
1.1 Light source
1.2 Sensor
1.3 Reservoir
1.4 Communication unit
1.5 Display
2. Main Server
2.1 Control unit
2.2 Data storage unit
2.3 Communication unit
Al. Artificial intelligence algorithm N. Sample Gl. Incident Ray Yl. Reflected Ray S. Spectrum N-ID. Sample identity 100. Method Detailed Description of the Invention:
The system (10) of the invention includes an apparatus (1) and a main server (2), to determine whether pharmaceutical finished products are counterfeit or not by analyzing which drug family (or active ingredient or drug substance) they belong to. The server (2) comprises at least one control unit (2.1), at least one wireless communication unit (2.3) enabling communication with an apparatus (1), and at least one data storage unit
(2.2) storing data belonging to a sample (N). The apparatus (1) comprises at least one light source (1.1) transmitting light at the predetermined near infrared wavelengths to the sample (N), at least one sensor (1.2) sensing the light reflected or transferred from the sample (N), at least one reservoir
(1.3) for positioning the sample (N) to the apparatus (1), at least one wireless communication unit (1.4) communicating with the main server (2) and at least one display (1.5) that enabling to display the data.
The system (10) of the invention includes at least one control unit (2.1), after optical scanning of the sample (N) positioned in an apparatus (1), controlling whether the sample (N) belongs to a predefined therapeutic family (or group) in the library in a data storage unit (2.2) by receiving the data after the data (i.e., received chemical fingerprint signal) received from the sensor (1 .2) which senses the NIR signal from said sample is transmitted to the main server (2) by means of a communication unit, determining the unidentified sample (N) family, i.e., identifying (or verifying the identified sample family) by determining the group with the highest match by correlation (matching) with all drugs in all groups registered in the data storage unit (2.2), and transmitting the data to the communication unit (1.4) included in the apparatus (1) via another communication unit (2.3) by not confirming if it is not a sample (N) belonging that family following the said control and enabling the said data to be displayed on the display (1.5) and on the other hand, confirming this if it belongs to the family and performing the transmitting similarly to the apparatus (1) and enabling this to be displayed on the display (1 .5) and therefore as a result of controls providing the confirmation whether the sample (N) is counterfeit or not, and therapeutic sample family.
Control unit (2.1) correlates (matches) each unknown drug with all groups registered in the data storage unit (2.2). This correlation can be done with the entire spectrum that includes the entire energy range from the sample, or can be done in a certain energy range specific to each group determined as the optimum range for that group. If the group contains only one drug product, rays in all wavelengths (in all energies) coming from the sample are used for correlation match. If the group contains more than one product, a correlation match is done in the optimum range specific to that group for each group predetermined by univariate or multivariate analysis. This optimum range can be a narrow wavelength (energy) range or can be in the range that includes the entire NIR region. Then, after the matching, the unknown sample (N) family is determined by the control unit (2.1) by determining the group with the highest match following the protocol represented in Figure 2 or if known, it is verified with the label.
In the invention, a portable spectroscopy apparatus (1) operating in reflection mode has been developed. The apparatus (1) included in the system of the invention can operate in the entire NIR range (800-2500 nm) and in all resolutions. In the invention, preferably a device (1) operating in the narrow wavelength range of 900 to 1700 nm has been developed. Thus, a much more cost-efficient, adoptable and scalable (or portable) apparatus (1) is provided in the invention with the apparatus (1) used in the preferred embodiment of the invention than those existing in the state of the art. The drug family determination algorithm and the drug family verification algorithm developed with the apparatus (1) complying with these criteria gives a 90% accuracy and a 95% accuracy, respectively. Better results can be obtained in a wider wavelength range and at high resolution.
Sample (N) is a pharmaceutical finished product in the preferred embodiment of the invention, although it varies according to the sectors. In another embodiment, the sample (N) is a pharmaceutical composition or any component of the pharmaceutical composition, such as active ingredient and/or excipient thereof.
Although the apparatus (1) included in the system (10) of the invention determines whether the pharmaceutical end products are counterfeit or not, it is not limited to this in practice. In the invention, it is determined which group of the NIR spectra registered in the library the pharmaceutical end product family (i.e., active ingredients thereof) belongs (or approximately belongs) to, which is obtained by sensing the ray reflecting (or scattering) from the sample (N) only by sending lights at certain wavelengths in the near infrared region to the sample (N) without using any consumables, and the sample (N) identity is determined accordingly. Therefore, the said analysis is carried out by a method (100) and the system (10) of the invention is operated with the said method (100). Specifically, the sample (N) analyzed intact and/or the sample (N) is not broken in order to receive signal from the sample (N) placed in the apparatus (1) of the invention and to reach the core of the sample (N) and therefore, the sample (N) identity is determined by determining the active ingredient class (or group). The method (100) of the invention has sufficient precision such that it carries out analysis over coatings of drug tablet products and over shells of capsule products and analyzes the drug substances within the capsules under the tablet coating. Therefore, the vibrational spectra in all embodiments of this invention are determined by the near infrared (NIR) spectroscopy technique and thereby it is ensured that pharmaceutical end products can be determined (identified) rapidly and/or verified by assessing the substantial and/or extensive chemical fingerprints of the said samples (N). This invention also determines the source or origin of counterfeit pharmaceuticals by following and comparing the chemical fingerprints. The method (100) of the invention operates according to the following method steps in order to analyze whether the drug is counterfeit or not by determining the chemical fingerprints of pharmaceutical substances:
-Transmitting the light at near infrared wavelengths to the sample (N) from one side using a light source (1 .1) (101)
-Determining and recording the chemical fingerprint (or spectrum) of the sample (N) by sensing the light (Yl) reflected or the light transferred from the sample (N) by a sensor (1.2) (102)
-Checking by the control unit (2.1) whether the spectrum of the sample (N) sent to the main server (2) by a communication unit (1.4) and the spectra of the drug families in the library (or a data storage unit) on the main server (2) match or not (103)
-If the sample (N) identity matches with a therapeutic supergroup (or label) existing in the library, giving clearance by the control unit (2.1) and enabling it to be displayed on a display (1 .5) by the control unit (2.1) (104)
-If the sample (N) identity does not match its label or cannot be identified by the system, exciting the other side of the sample (N) with the light source (1.1) and determining and recording the chemical fingerprint (spectrum) from the second side of the sample (N) with the ray (Yl) reflecting from the sample (N) sensed by the sensor (1.2) mentioned in step 102 (105) -Checking by the control unit (2.1) whether the identity of the sample (N) sent to the main server (2) by a communication unit (1.4) and any drug family (or therapeutic supergroup) in the library on the main server (2) match or not (106) -If the family identity of the sample (N) matches with a drug substance family existing in the library, giving clearance by the control unit (2.1) (107)
-If the identity of the sample (N) does not match with any drug family in the library, failure to identify the sample (N) family or if the sample (N) matches with a drug family in the library, but this match does not match with the sample (N) label, checking by the control unit (2.1) whether the sample (N) is the first sample (N) or not (108)
-If the said sample (N) is the second or more samples (N), not giving clearance by the control unit (2.1) and determining that the sample (N) is counterfeit (109) -If the said sample (N) is the first sample (N) and not given clearance by the control unit (2.1), requesting to select another sample (N) and repeating all steps starting from step 101 for other sample (N) (or specimen) (110)
As mentioned in steps 104 and 107, if the specific product analyzed exists in the library (or database), and the drug family of the product is desired to be validated, the evaluation proceeds as follows:
-If the threshold value of the product (or sample or specimen) is above a predetermined value for example 95%, (a) and
-If the match result after step (a) is the same with the product specified on the label, the product passes the test
-If the match result after step (a) is not the same with the product specified on the label, the product fails the test and is transferred to the laboratory as a suspected product
To give an example for this embodiment: Drug having the brand name Lipitor is a drug from the "atorvastatin" family. When the Lipitor tablet is desired to be analyzed, the Lipitor spectrum to be tested is compared with the spectra of the products in the database. As a result of the comparison, the sample (N) fails the test in two cases. First, if the highest similarity index calculated for the Lipitor sample tested is below 95% or secondly, if the similarity index is above the threshold (i.e.> 95%) but the sample (N) is not identified belonging to the "atorvastatin" therapeutic supergroup then the sample (N) is considered suspected as well and is sent to the laboratory for further testing. As mentioned in steps 105 and 108, if the specific sample analyzed does not exist in the database, but at least one or more products belonging to (i.e. having the same active ingredient) the sample family exists in the library (or database), the evaluation proceeds as follows:
-The lowest similarity index is at a predetermined value, for example at least 70% (only one threshold value being 70% is sufficient). All products below this threshold value are reported as unidentified. That is, the system reports that these products are unidentified).
-If the similarity index value is a predetermined value for example 70% or a higher value, looking at the similarity (correlation) index obtained from the first three matches and/or the ratio of similarity index rates to each other (lower value/higher value)
Current situations in this last step can be as follows:
1.Situation: If the similarity (correlation) index obtained from the first three matches is from the same family, then the product family is determined. (Table-1)
2.Situation: If the similarity (correlation) index found after the first three matches corresponds to at least one different product family, and these similarity index rates (lower value/higher value) are similar %98 to each other, then the sample (N) is regarded as belonging to any of these three families. So it is stated that there are three possibilities.
3.Situation: If the similarity (correlation) index found after the first three matches corresponds to at least one different product family, and these similarity index rates (lower value/higher value) are less than 98% and the highest similarity index is above 85%, then the sample family is regarded as the class with the highest similarity index.
Figure imgf000012_0001
Figure imgf000013_0001
Figure imgf000014_0001
Table-1
The method (100) of the invention, in a narrow region (900-1700 nm) where less spectral information is available, identifies the product family with more than 90% accuracy and verify it with more than 95% accuracy using the grouping approach.
Grouping approach is the initial grouping by placing as many different formulations as possible from the same drug substance family in the same therapeutic supergroup (i.e., the same API bucket). The invention is a very simple and one-step model compared to the prior arts. It should be understood that by a one-step model is meant each new product is placed directly to their therapeutic supergroup (or buckets or groups). If the sample (N) is a product whose family does not exist in the library, then a new bucket or group is added. Each new drug is added to its supergroup in a single and large database, and the identity of the drug family is determined by running a correlation algorithm. Therefore, each drug is added to its supergroup in the data storage unit (2.2) included in the main server (2). Accordingly, each unknown drug is correlated (matched) with all drugs in all groups by the control unit (2.1). Then, the unidentified sample (N) family is determined by the control unit (2.1) by determining the group with the highest match obtained from the match.
The said algorithm identifies and/or verifies the active ingredient of a drug without any prior knowledge of the drug. Exemplary pharmaceutical product groups (or buckets) for some drug substances are given below:
Figure imgf000015_0001
The groups in the said table and the pharmaceutical end products belonging to the group are not limited to those listed.
Industrial Applicability:
The method (100) of the invention and the system (10) operating based on the said method (100) have industrial applicability, especially for use in identifying the drugs in the pharmaceutical field. The invention is not limited to the exemplary embodiments above, and a person skilled in the art can easily put forth other different embodiments of the invention. These should be considered within the scope of protection of the invention claimed by the claims.

Claims

1. A method (100) for determining the identity of the pharmaceutical end products
(drug substance or therapeutic drug family group) and whether they are counterfeit or not according to the said identity, characterized in that it comprises:
- Transmitting the light at near infrared wavelengths to the sample (N) from one side using a light source (1.1) (101)
- Determining and recording the chemical fingerprint (or spectrum) of the sample (N) by sensing the light (Yl) reflected or the light transferred from the sample (N) by a sensor (1.2) (102)
- Checking by the control unit (2.1) whether the spectrum of the sample (N) sent to the main server (2) by a communication unit (1.4) and the spectra of the drug families in the library (or a data storage unit) on the main server (2) match or not (103) - If the sample (N) identity matches with a drug group (or label) existing in the library, giving clearance by the control unit (2.1) and enabling it to be displayed on a display (1.5) by the control unit (2.1) (104)
- If the sample (N) identity does not match or cannot be identified with the existing label, exciting the other side of the sample (N) with the light source (1.1) and determining and recording the chemical fingerprint (spectrum) from the second side of the sample (N) with the ray (Yl) reflecting from the sample (N) sensed by the sensor (1.2) mentioned in step 102 (105)
- Checking by the control unit (2.1) whether the identity of the sample (N) sent to the main server (2) by a communication unit (1 .4) and any drug family (or drug substance group) in the library on the main server (2) match or not (106)
- If the family identity of the sample (N) matches with a drug substance family existing in the library, giving clearance by the control unit (2.1) (107)
If the identity of the sample (N) does not match with any drug family in the library, failure to identify the sample (N) family or if the sample (N) matches with a drug family in the library, but this match does not match with the sample (N) label, checking by the control unit (2.1) whether the sample (N) is the first sample (N) or not (108)
- If the said sample (N) is the second or more samples (N), not giving clearance by the control unit (2.1) and determining that the sample (N) is counterfeit (109) If the said sample (N) is the first sample (N) and not given clearance by the control unit (2.1), requesting to select another sample (N) and repeating all steps starting from step 101 for other sample (N) (or specimen) (110).
2. A method (100) according to claim 1 , characterized in that the evaluation proceeds according to the following steps, if the specific product analyzed exists in the library (or database), and the drug family of the product is desired to be validated, as mentioned in steps 104 and 107;
- If the threshold value of the product (or sample or specimen) is above a predetermined value for example 95 %, (a) and
- If the match result after step (a) is the same with the product specified on the label, the product passes the test
- If the match result after step (a) is not the same with the product specified on the label, the product fails the test and is transferred to the laboratory as a suspected product.
3. A method (100) according to any one of preceding claims, characterized in that the evaluation proceeds according to the following steps, if the specific sample analyzed does not exist in the database, but at least one or more products belonging to (i.e. having the same active ingredient) the sample family exists in the library (or database), as mentioned in steps 105 and 108;
- The lowest similarity index is at a predetermined value, for example at least 70%,
If the similarity index value is a predetermined value for example 70% or a higher value, looking at the similarity (correlation) index obtained from the first three matches and/or the ratio of similarity index rates to each other (lower value/higher value).
4. A system (10) operating according to the method steps of any one of preceding claims, for determining whether the pharmaceutical end products are counterfeit or not by determining which drug family they belong, comprising;
- a server (2) comprising at least one control unit (2.1), at least one wireless communication unit (2.3) enabling communication with an apparatus (1), and at least one data storage unit (2.2) storing data belonging to a sample (N), and further an apparatus (1) comprising at least one light source (1.1) transmitting light at the predetermined near infrared wavelengths to the sample (N), at least one sensor (1.2) sensing the light reflected or transferred from the sample (N), at least one reservoir (1 .3) for positioning the sample (N) to the apparatus (1), at least one wireless communication unit (1 .4) communicating with the main server (2) and at least one display (1.5) enabling to display the data and further at least one control unit (2.1), after optical scanning of the sample (N) positioned in the said apparatus (1), controlling whether the sample (N) belongs to a predefined therapeutic family (or group) in the library in a data storage unit (2.2) by receiving the data after the data (i.e., received chemical fingerprint signal) received from the sensor (1.2) which senses the NIR signal from said sample (N) is transmitted to the main server (2) by means of a communication unit, determining the pharmaceutical family of the unidentified sample (N), i.e., identifying by determining the group with the highest match by correlation (matching) with all drugs in all groups registered in the data storage unit (2.2), and transmitting the data to the communication unit (1.4) included in the apparatus via another communication unit (2.3) by not confirming if it is not a sample (N) belonging that family following the said control and enabling the said data to be displayed on the display (1.5) and on the other hand, confirming this if it belongs to the family and performing the transmitting similarly to the apparatus (1) and enabling this to be displayed on the display (1 .5) and therefore as a result of the said controls providing the confirmation whether the sample (N) is counterfeit or not.
5. A system (10) according to claim 4, characterized by a portable spectroscopy apparatus (1) operating in the reflection mode that includes the NIR region.
6. A system (10) according to claim 5, characterized by an apparatus (1) operating in the wavelength range of 800-2500 nm.
7. A system (10) according to claim 6, characterized by an apparatus (1) operating in the narrow wavelength range of 900 to 1700 nm.
PCT/TR2021/050337 2021-04-09 2021-04-09 A pharmaceutical product identification method and a system operating based on the said method WO2022216244A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/TR2021/050337 WO2022216244A1 (en) 2021-04-09 2021-04-09 A pharmaceutical product identification method and a system operating based on the said method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/TR2021/050337 WO2022216244A1 (en) 2021-04-09 2021-04-09 A pharmaceutical product identification method and a system operating based on the said method

Publications (1)

Publication Number Publication Date
WO2022216244A1 true WO2022216244A1 (en) 2022-10-13

Family

ID=83545624

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/TR2021/050337 WO2022216244A1 (en) 2021-04-09 2021-04-09 A pharmaceutical product identification method and a system operating based on the said method

Country Status (1)

Country Link
WO (1) WO2022216244A1 (en)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120012750A1 (en) * 2007-08-08 2012-01-19 Eran Sinbar Thermography based system and method for detecting counterfeit drugs
US20160047787A1 (en) * 2012-12-31 2016-02-18 Omni Medsci, Inc. Short-wave infrared super-continuum lasers for detecting counterfeit or illicit drugs and pharmaceutical process control
US20200182781A1 (en) * 2018-12-10 2020-06-11 Kerloss Sadek Mobile spectrum analyzer systems and methods

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120012750A1 (en) * 2007-08-08 2012-01-19 Eran Sinbar Thermography based system and method for detecting counterfeit drugs
US20160047787A1 (en) * 2012-12-31 2016-02-18 Omni Medsci, Inc. Short-wave infrared super-continuum lasers for detecting counterfeit or illicit drugs and pharmaceutical process control
US20200182781A1 (en) * 2018-12-10 2020-06-11 Kerloss Sadek Mobile spectrum analyzer systems and methods

Similar Documents

Publication Publication Date Title
Biancolillo et al. Chemometric methods for spectroscopy-based pharmaceutical analysis
US7218395B2 (en) Rapid pharmaceutical identification and verification system
US20060086901A1 (en) Methods and apparatus for improving the reliability and accuracy of identifying, analyzing and authenticating objects, including chemicals, using multiple spectroscopic techniques
CN108254351B (en) Raman spectrum detection method for checking articles
US8719043B2 (en) Drug authentication
Dégardin et al. Comprehensive Study of a Handheld Raman Spectrometer for the Analysis of Counterfeits of Solid‐Dosage Form Medicines
US20060015536A1 (en) Database and method of use for authenticity verification of pharmaceuticals
Rodionova et al. Quantitative risk assessment in classification of drugs with identical API content
US20050288906A1 (en) Spectroscopic pharmacy verification and inspection system
US9013686B2 (en) Chemical and molecular identification and quantification system utilizing enhanced photoemission spectroscopy
CN111141719A (en) Rapid nondestructive identification method for anti-AIDS medicine
US20200182781A1 (en) Mobile spectrum analyzer systems and methods
Fuenffinger et al. Classification of ciprofloxacin tablets using near-infrared spectroscopy and chemometric modeling
Kakio et al. Classification and visualization of physical and chemical properties of falsified medicines with handheld Raman spectroscopy and X-ray computed tomography
Paraskevaidi et al. Aluminium foil as an alternative substrate for the spectroscopic interrogation of endometrial cancer
Chen et al. Express detection of expired drugs based on near-infrared spectroscopy and chemometrics: A feasibility study
Waffo Tchounga et al. Usefulness of medicine screening tools in the frame of pharmaceutical post-marketing surveillance
Baik et al. Pharmaceutical tablet classification using a portable spectrometer with combinations of visible and near-infrared spectra
Paolanti et al. Automatic classification for anti mixup events in advanced manufacturing system
WO2022216244A1 (en) A pharmaceutical product identification method and a system operating based on the said method
Usman et al. Applications of miniaturized and portable near infrared (NIR), Fourier transform infrared (FT-IR) and Raman spectrometers for the inspection and control of pharmaceutical products
Ralbovsky et al. Raman spectroscopy and multivariate analysis for identification and classification of pharmaceutical pain reliever tablets
Kalyanaraman et al. Portable spectrometers for pharmaceutical counterfeit detection
RU2685758C1 (en) Method of performing tableted medicinal preparations in blister packing by nir spectrometry
Dégardin et al. Innovative strategy for counterfeit analysis

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21936186

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 25.01.2024)