Course

Unit 1

a. Computers in Pharmaceutical Research and Development: A General Overview: History of Computers in Pharmaceutical Research and Development.

Statistical modeling in Pharmaceutical research and development: Descriptive versus Mechanistic Modeling,

Statistical Parameters, Estimation, Confidence Regions, Nonlinearity at the Optimum, Sensitivity Analysis, Optimal Design

Population Modeling

b. Quality-by-Design In Pharmaceutical Development:

Introduction, ICH Q8 guideline, Regulatory and industry views on QbD,

Scientifically based QbD – examples of application.

Unit 2

Computational Modeling Of Drug Disposition:

Introduction ,Modeling Techniques: Drug Absorption, Solubility, Intestinal Permeation, Drug Distribution ,Drug Excretion,

Active Transport; P-gp, BCRP, Nucleoside Transporters, hPEPT1, ASBT, OCT, OATP, BBB-Choline Transporter.

Unit 3

Computer-aided formulation development:

Concept of optimization, Optimization parameters, Factorial design

Optimization technology & Screening design

Computers in Pharmaceutical Formulation: Development of pharmaceutical emulsions,(1hr)

microemulsion, drug carriers (1hr)

Legal Protection of Innovative Uses of Computers in R&D, The Ethics of Computing in Pharmaceutical Research, Computers in Market analysis

Unit 4

a. Computer-aided biopharmaceutical characterization: Gastrointestinal absorption simulation. Introduction, Theoretical background, Model construction,

a. Computer-aided biopharmaceutical characterization: Gastrointestinal absorption simulation. Introduction, Theoretical background, Model construction,

Parameter sensitivity analysis,

Parameter sensitivity analysis,

Unit 5

Robotics and Computational fluid dynamics: General overview,(4hrs) Pharmaceutical Automation,(4hrs) Pharmaceutical applications, Advantages and Disadvantages.(2hrs) Current Challenges and Future Directions.(2hrs)

This course deals with computer applications in pharmaceutical product research and development. Students are able to understand computers across the entire drug delivery research and development process. So that they can equip themselves to industrial and research environments where computational modelling is widely explored. Basic theoretical discussions of the principles of computational modelling from classical statistics-based systems such as the design of experiments to advanced artificial intelligence such as Neural networks and Genetic algorithm-based systems are taught.

Students are educated to develop quality-by-design systems to resolve specific pharmaceutical challenges. They explore different optimal designs to minimize laboratory optimization experiments. They familiarized with in-silico modelling to predict the ADME profile of pharmaceuticals. They also learn about PK& PD simulation at different levels from organ to gene. Students learn about the fundamentals of artificial intelligence (AI) in revolutionizing the formulation and development of modern pharmaceuticals, optimising drug design, developing formulations, ability to analyse large data sets and streamline clinical trials more accurately and efficiently. In conclusion, the students are learning the emerging fields of simulation and AI for pharmaceutical formulation and development.

Objectives

Upon completion of this course, it is expected that students will be able to

KNOWLEDGE:

K1: Discuss current status and future perspectives of application of computers in pharmaceutical field.

K2: Explain computational Modeling of Drug Disposition.

K3: Describe Computers in Preclinical Development.

K4: Differentiate role of different active transporters.

K5: Apply the principles of DOE for formulation development

K6: Elaborate Computational fluid dynamics (CFD)

SKILL:

S1: Design QbD for pharmaceutical quality and risk management

S2: Develop optimal design for pharmaceutical formulation.

S3: Predict drug disposition by computational modeling. S4: Identify active transporter.

S5: Develop pharmaceutical formulations using computer.

ATTITUDE:

A1. Maintain classroom decorum.

A2. Keep your attention in class.

A3. Follow the value of lifelong learning.

A 4. Participate actively in class discussions. A 5. Maintain polite and humble behaviour A 6. Show kindness to our fellow beings.

1. Classify population modeling
2. Discuss industrial quality by design system
3. Expression of active transporters in different patho-physiological conditions: examples and relevance
4. Eleborate factorial designs
5. Construct model for gastrointestinal absorption
6. Challenges and opportunities in computer simulations of pharmacokinetics and pharmacodynamics
7. Discuss role of artificial Intelligence in product

Journals:

Methods in molecular biology Journal of Controlled Release

International Journal of Pharmaceutics Cell Chemical Biology

Journal of Drug Delivery Science and Technology

References Books

1. Computer Applications in Pharmaceutical Research and Development,Sean Ekins, 2006, John Wiley & Sons.
2. Computer-Aided Applications in Pharmaceutical Technology, 1st Edition, Jelena Djuris, Woodhead Publishing
3. Encyclopedia of Pharmaceutical Technology, Vol 13, James Swarbrick, James. Boylan, Marcel Dekker Inc, New York, 1996.
4. A. Saharan Computer Aided Pharmaceutics and Drug Delivery, An Application Guide for Students and Researchers of Pharmaceutical Sciences. Published by Springer Nature Singapore Pte Ltd. 2022