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CPT: pharmacometrics & systems pharmacology
05, 2024;13 (5): 691-709.

Realizing the promise of Project Optimus: Challenges and emerging opportunities for dose optimization in oncology drug development.

Wei Gao, Jiang Liu, Blerta Shtylla, Karthik Venkatakrishnan, Donghua Yin, Mirat Shah, Timothy Nicholas, Yanguang Cao
Author Information
  1. Wei Gao: Quantitative Pharmacology, EMD Serono Research & Development Institute, Inc., Billerica, Massachusetts, USA. ORCID
  2. Jiang Liu: Food and Drug Administration, Silver Spring, Maryland, USA.
  3. Blerta Shtylla: Quantitative Systems Pharmacology, Pfizer, San Diego, California, USA.
  4. Karthik Venkatakrishnan: Quantitative Pharmacology, EMD Serono Research & Development Institute, Inc., Billerica, Massachusetts, USA. ORCID
  5. Donghua Yin: Clinical Pharmacology, Pfizer, San Diego, California, USA.
  6. Mirat Shah: Food and Drug Administration, Silver Spring, Maryland, USA.
  7. Timothy Nicholas: Pharmacometrics, Pfizer, Groton, Connecticut, USA.
  8. Yanguang Cao: Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. ORCID
PMID: 37969061 DOI: 10.1002/psp4.13079

Abstract

Project Optimus is a US Food and Drug Administration Oncology Center of Excellence initiative aimed at reforming the dose selection and optimization paradigm in oncology drug development. This project seeks to bring together pharmaceutical companies, international regulatory agencies, academic institutions, patient advocates, and other stakeholders. Although there is much promise in this initiative, there are several challenges that need to be addressed, including multidimensionality of the dose optimization problem in oncology, the heterogeneity of cancer and patients, importance of evaluating long-term tolerability beyond dose-limiting toxicities, and the lack of reliable biomarkers for long-term efficacy. Through the lens of Totality of Evidence and with the mindset of model-informed drug development, we offer insights into dose optimization by building a quantitative knowledge base integrating diverse sources of data and leveraging quantitative modeling tools to build evidence for drug dosage considering exposure, disease biology, efficacy, toxicity, and patient factors. We believe that rational dose optimization can be achieved in oncology drug development, improving patient outcomes by maximizing therapeutic benefit while minimizing toxicity.

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MeSH Term

Humans
Drug Development
Antineoplastic Agents
Neoplasms
United States
United States Food and Drug Administration
Dose-Response Relationship, Drug
Journal Article Review
Article has an altmetric score of 13

Word Cloud

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