The workshop is neither trying to provide a 101 course on LC-MS proteomics nor attempts to focus on what is new in LC-MS proteomics techniques. Attendees need to have some background but not necessarily leading experts in the field. The consensus report from the previous ISSX Workshop held in 2018 (Prasad et al. 2019, Clinical Pharmacology and Therapeutics) is considered a background reading. The recent Symposium Repot from North American ISSX 2023 in Boston (Prasad et al 2024, Drug Metabolism Disposition, In Press) captures the content of lectures and workshop exercises. Hence, the event builds on what is known in the literature in relation to LC-MS proteomics and provides more practical guidance for those who are expanding their research activities in this area, such that they do not go through pitfalls and get to the end point faster.

This webinar will introduce dynamic free fraction (fd) as a new concept characterizing drug protein binding and demonstrate the utility of fd in hepatic clearance mediated by CYP and OATP transporter.

This webinar is intended to raise the awareness of complicated scenario where drug-drug-disease interaction occurs and how to evaluate the PK of drugs using PBPK to inform the optimal use of drugs in such patient group.

In this webinar we will discuss efforts for improving the global underrepresentation of African genetics in science. We will further explore the current landscape and challenges in realizing an African hepatic modeling platform - with a specific focus on the development of hiPSC models that can better recapitulate hepatic function.

This symposium/webinar is intended to educate ADME scientists on MPS technology and its potential to generate clinically translatable data.

The human genome comprises approximately 20,000 protein-coding genes and over 900 million variants according to dbSNP. Systematic understanding of the impact of genomic alterations in humans is critical for the development of effective medicines. However, it is simply not feasible to study every single variant in detail. This challenge extends to the analysis of how pharmacogenes are affected by genetic polymorphisms, as it is impossible to study the impact of every individual single nucleotide polymorphisms/variations (SNPs/SNVs) of pharmacogenes in human clinical trials. Yet, understanding drug metabolism and pharmacokinetics is crucial for assessing drug efficacy and safety. To minimize harmful side effects from drugs while maximizing their therapeutic effectiveness in each patient or group of patients, we would need to understand the effects of population specific SNPs in pharmacogenes and drug-enzyme interactions. To date the effect of non-synonymous SNPs, more specifically missense mutations, at the protein level is poorly studied in pharmacogenomics research. We previously proposed a post-hoc analysis approach of molecular dynamics (MD) simulations using dynamic residue network (DRN) analysis to consider the dynamic nature of functional proteins and protein-drug complexes and to probe the impact of mutations and their allosteric effects. This talk will discuss the computational approaches and tools that we have developed over the years with applications to pharmacogenomics.