Theme 1: Predictive Biomarker Strategies to De-Risk Drug Development
Translational researchers are advancing more predictive and efficient strategies with an aim to predict, reduce, and nullify potential risk in drug development from early drug discovery through late-stage clinical trials. Alteration of drug-metabolizing enzymes or drug transporters can have a significant effect on drug disposition and exposure, leading to drug-drug interactions (DDIs) or drug-induced organ toxicity, which can lead to termination of candidate drug development. Predictive biomarkers can be useful in early drug development to assess drug-induced organ toxicity, DDIs, and to understand PK variations in subjects with genetic polymorphism or organ impairment. PD biomarkers can be useful to inform drug response and dose selection. Some PD biomarkers can ultimately be used for approval. For example, the recent approval of Aducanumab relies heavily on biomarker of PET imaging for amyloid plaque change. This theme covers the application of advances in technology and techniques that discuss the discovery and qualification of predictive biomarkers for PD, DDIs, patient selection, and organ toxicity.
Theme 2: Advancing Innovation in In Silico Translational Approaches
The objectives of this theme are to discuss advancement and application of in silico quantitative approaches in the preclinical phase to post-approval to support development of new targets/modality, reduce the use of animals, improve clinical study design, and optimize therapeutic individualization. For example, in silico modeling and simulations can be very useful in supporting recent FDA Project Optimus, emphasizing characterization of dose-response for oncology.
Submissions are encouraged to cover research and development that enable advancing translational science approaches such as: in silico modeling and simulation; use of machine learning to inform clinical trial design; physiological based PK modeling applications (e.g., bridging formulations, biowaivers); first-in-human dose prediction for novel modalities that do not have good preclinical models; and the translational aspects of preclinical immunogenicity data to humans. Case studies translating application of such tools to the clinic are encouraged.
Theme 3: Novel Predictive Preclinical Models for Efficacy and Toxicology
Successful clinical drug development relies on effective preclinical testing. Large-scale or mechanism-based in vitro testing and the ability to combine proteomic, metabolomic and other novel technologies can speed up the development of more effective and safer drugs. Preclinical testing is constantly evolving especially with advancements in biotechnology resulting in development of novel modalities and increased understanding of disease and drug metabolism mechanisms. Further, FDA Modernization Act 2.0 may lead to changes in nonclinical testing and strategies, which could inspire new approaches for in vitro assays and models to predict clinical efficacy/safety. Some examples of new preclinical models are patient-derived xenograft models, 3-D organoids in cancer therapy development, and organ-on-a-chip for potency and toxicity evaluation. This theme will share cutting-edge preclinical testing systems for better translation of preclinical drug metabolism, efficacy or toxicity data to the clinic.
2023 AAPS PharmSci 360 Exhibit and Sponsorship Opportunities
Exhibiting and sponsorship opportunities are now available! Booth and non-booth packages are available to meet the business goals of scientific leadership, lead generation, brand awareness, and product/service demonstration. To Learn more or contact Rich Hodge at SalesAAPS@ntpevents.com.