COMPUTATIONAL MODELING OF DRUG DISPOSITION AND 21CFR11 .pptx

The presentation discusses the challenges in drug discovery, particularly regarding drug candidates' pharmacokinetic properties such as Absorption, Distribution, Metabolism, and Toxicity (ADMET). Historically, drug discovery focused more on efficacy and selectivity, but undesirable ADMET properties have led to high failure rates in clinical trials, particularly in phases 2 and 3.

To address this, in vitro evaluation and high-throughput ADMET property screening assays like Caco-2 and MDCK cell monolayers are now widely used in early drug discovery stages to predict ADMET properties even before compounds are synthesized.

Key Concepts:
Modeling Techniques:

Quantitative Approaches:
Uses methods like pharmacophore modeling and flexible docking to understand drug interactions with targets. Examples include DISCO, GASP, and HIPOP/CATALYST.
Qualitative Approaches:
Uses QSAR and QSPR to correlate molecular descriptions with ADMET properties, utilizing statistical algorithms like Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM).
Regulatory Considerations (21 CFR Part 11):

This section focuses on FDA regulations regarding electronic records and signatures in industries like pharmaceuticals. It includes general provisions, electronic records management, and electronic signature requirements.

1. TOPIC:- COMPUTATIONAL MODELING OF DRUG DISPOSITION UTTARANCHAL INSTITUTE OF PHARMACEUTICAL SCIENCES UTTARANCHAL UNIVERSITY, PREM NAGAR, DEHRADUN 248001, UTTARAKHAND MADE BY:- PRAMESH PANWAR

2. COMPUTATIONAL MODELING OF DRUG DISPOSITION Historically, drug discovery focused exclusively on efficacy and selectivity against the biological target. As a result, half of the drug candidates fail in phase 2 and 3 clinical trials because of undesirable drug pharmacokinetics properties including absorptions, distribution, metabolism, and toxicity (ADMET). To reduce the attrition rate at more expensive later stages, in vitro evaluation and ADMET properties in the early phase of drug discovery have been widely adopted. Many high-throughput in vitro ADMET property screening assays have been developed and applied successfully. For example:- Caco-2 and MDCK cell monolayers-------- Applied to predict the ADMET properties of compounds even before they are synthesized.

3. MODELING TECHNIQUE 1. Quantitative approaches It is represented by pharmacophore modelling and flexible docking studies Investigate The structural requirement for the interaction between drugs and the targets that are involved in the ADMET process. These are useful– when there is an accumulation of knowledge against a certain target. Widely used- DISCO (Distance comparisons) GASP – (Genetic Algorithm similarity program) HIPOP/ CATALYST 2. Qualitative approaches It is represented by – QSAR (Quantitative structure-activity relationship) and QSPR (Quantitative structure-property relationship) Analysis To correlate molecular descriptions with ADMET-related properties With the help of statistical algorithms Examples:- MLR (Multiple linear regression) ANN (Artificial neural network) SUM (Support vector machine)

4. 21 CFR 11

5. 21 CFR 11 21 CFR 11 CFR:- Code of Federal Regulations Title 21:- Is the concern with the area of Food and Drugs Part 11- It is a sub-section. It focuses on specific areas (electronic Records and electronic signatures) Each title is divided into chapters, subchapters, parts, and sections. SUBPART A- GENERAL PROVISIONS 11.1- Scope 11.2 - Implementation 11.3 - Definitions SUBPART A- ELECTRONIC RECORDS 11.10- Control for a closed system 11.30 - Control for open system 11.70 - Signature / Record linking SUBPART C- ELECTRONIC SIGNATURE 11.100- General requirement 11.200 - electronic signature components 11.300 - Identification codes/passwords 21 CFR Part 11 is a part of the Code of Federal Regulations that establishes the United States Food and Drug Administration's (FDA) regulations on electronic records and electronic signatures (ERES). The rule applies to all aspects of electronic records management in industries regulated by the FDA, including pharmaceuticals, medical devices, biotech, and food companies.

6. SUBPART A:- GENERAL PROVISIONS 11.1- SCOPE:- Electronic records are to be trustfully reliable and generally equivalent to paper records. Electronic signature to be equivalent to handwritten signatures, and other general signing. 11.2- IMPLEMENTATION:- For records must be maintained but not submitted to the agency provided that the requirements of these parts are met. 11.3- DEFINITION:- Electronic records:- Combination of text, graphic data, audio, etc. Electronic signature: a digital representation of a person’s handwritten signature. Biometric:- Verifying individual identity based on individual physical features.

7. SUBPART B:- ELECTRONIC RECORDS 11.10 CONTROL FOR CLOSED SYSTEM:- A closed system is controlled by a person responsible for electronic records stored on it. To ensure the authenticity, integrity, and procedures. 11.30- CONTROL FOR OPEN SYSTEM:- An open system to which a is not controlled by those responsible for the electronic records stored on it. People responsible for data content also control systems. 11.70- SIGNATURE / RECORD LINKING:- The electronic signature and the handwritten sign shall be linked to their respective electronic records to ensure that the signatures can not be excised, copied, or otherwise transferred to falsify.

8. SUBPART C:- ELECTRONIC SIGNATURE 11.100 – GENERAL REQUIREMENT Unique Verify the identity Certify 11.200- ELECTRONIC SIG. COMPONENTS NON-BIOMETRIC:- Does not involve the use of biological characteristics or traits for identification authentication or verification purposes. In contrast to biometric methods, which rely on unique physiological or behavioral attributes of individuals (such as fingerprints, facial recognition, iris patterns, voiceprints) 11.300-CONTROLS FOR IDENTIFICATION CODES / PASSWORDS It includes:- uniqueness Codes and passwords Periodic testing of devices

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