Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine.

Journal: Expert opinion on drug metabolism & toxicology
PMID: 38480460

Abstract

INTRODUCTION: Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hampers accurate prediction of drug candidates' pharmacokinetic properties.

Authors

  • Ajita Paliwal
    Department of Pharmacy, School of Medical and Allied Sciences, Galgotias University, Greater Noida, India.
  • Smita Jain
    Department of Pharmacy, Banasthali Vidyapith, Banasthali, India.
  • Sachin Kumar
    Department of Pharmacology, Delhi Institute of Pharmaceutical Sciences and Research, University of Delhi, New Delhi, India.
  • Pranay Wal
    Department of Pharmacy, Pranveer Singh Institute of Technology, Pharmacy, Kanpur, India.
  • Madhusmruti Khandai
    Department of Pharmacy, Royal College of Pharmacy and Health Sciences, Berahmpur, India.
  • Prasanna Shama Khandige
    NGSM Institute of Pharmaceutical Sciences, Department of Pharmacology, Manglauru, NITTE (Deemed to be University), Manglauru, India.
  • Vandana Sadananda
    AB Shetty Memorial Institute of Dental Sciences, Department of Conservative Dentistry and Endodontics, NITTE (Deemed to be University), Mangaluru, India.
  • Md Khalid Anwer
    Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia.
  • Monica Gulati
    School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, India.
  • Tapan Behl
    Amity School of Pharmaceutical Sciences, Amity University, Mohali, Punjab, India.
  • Shriyansh Srivastava
    Department of Pharmacy, School of Medical and Allied Sciences, Galgotias University, Greater Noida, India.

Keywords

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