Model informed drug discovery and development (MID3) is a paradigm of data analytics in drug development which facilitates the development and application of various quantitative approaches like exposure-response, biological, and statistical models to characterize pre-clinical and clinical data. MID3 is usually aimed at improving the quality, efficiency and cost effectiveness of decision making in drug development. The knowledge and inferences from this quantitative framework help in making informed decisions for dosage optimization and provide supportive evidence for efficacy, clinical trial design, and informing policies. MID3 approach enables multidimensional integration of data across targets/mechanisms of actions, molecules/drugs, doses/regimens, indications, trial designs, endpoints, and patient characteristics/populations.1
Model based meta-analysis is an important quantitative toolkit in MID3. MBMA is different from conventional meta-analysis as MBMA helps to integrate concepts of pharmacology and biology with statistical concepts.2,3
MBMA serves a range of purposes such as:
Use of MID3 approaches are increasing as the wide applications of them are established and are also gaining acceptance and interest from regulatory authorities.4 MBMA has proven applications in the complete life cycle of drug discovery and development from early development activities like candidate and target selection, early clinical phase decisions on candidate development and trial design to decisions during late clinical phase and post approval .1,3
Identifying and preparing essential metadata available from the public domain of biomedical literature, specific to the analysis objective for MBMA requires voluminous efforts.
Excelra’s expert clinical pharmacology group is helping the Quantitative Pharmacology and Pharmacometrics groups of pharmaceutical companies in building MBMA analysis specific datasets. This is performed with robust and customized, systematic literature review (SLR), following the industry-accepted PICOS methodology.
"The Case of Competitive Landscape & Go/No-go Clinical Trial Decision for a Big Pharma"
Objective
To identify the probability of the success of a new therapeutic antibody for Rheumatoid Arthritis.
About the Client
Client Specification
The client wanted to assess the relative efficacy of its antibody, against competitor marketed biologics for Rheumatoid Arthritis. A customized MBMA friendly dataset was to be developed by curating existing evidence on the efficacy of marketed biologics for Rheumatoid Arthritis.
Model informed drug discovery and development (MID3) is an integral part of drug development, especially model based meta analysis (MBMA), where information from published literature is leveraged to learn from the past experience and optimize future clinical trial design.
For more information
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