Artificial Intelligence for Quantitative Modeling in Drug Discovery and Development: An Innovation & amp; Quality (IQ) Consortium Perspective on Use Cases and Best Practices

Clin Pharmacol Ther. 2023 Sep 16. doi: 10.1002/cpt.3053. Online ahead of print.ABSTRACTRecent breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML) have ushered in a new era of possibilities across various scientific domains. One area where these advancements hold significant promise is model-informed drug discovery and development (MID3). To foster a wider adoption and acceptance of these advanced algorithms, the Innovation & Quality (IQ) Consortium initiated the AI/ML working group (WG) in 2021 with the aim of promoting their acceptance among the broader scientific community as well as by regulatory agencies. By drawing insights from workshops organized by the WG and attended by key stakeholders across the biopharma industry, academia, and regulatory agencies, this white paper provides a perspective from the IQ Consortium. The range of applications covered in this white paper encompass the following thematic topics: (1) AI/ML-enabled Analytics for Pharmacometrics & QSP Workflows; (2) Explainable Artificial Intelligence and its Applications in Disease Progression Modeling; (3) Natural Language Processing (NLP) in Quantitative Pharmacology Modeling; (4) AI/ML Utilization in Drug Discovery. Additionally, the paper offers a set of best practices to ensure an effective and responsible use of AI, including considering the context of use, explainability and generalizability of models, and having human-in-the-loop. We believe that embracing the transformat...
Source: Clinical Pharmacology and Therapeutics - Category: Drugs & Pharmacology Authors: Source Type: research