See how we’ve enabled a virtuous cycle of pre-clinical intelligence, with solutions for discovery, toxicology, and AI-powered biosimulation and QSP modeling.
Whether you’re a pre-clinical scientist, a clinical leader, or simply born innovator, this is a prime opportunity to discover how Certara’s products and services can unlock efficiencies and intelligence earlier in the development journey, for faster and more economical advancement of promising leads.
Welcome and Orientation to the Day
Starting with the End in Mind: Strategy from TPP to Clinic
How do we measure pre-clinical success? Ultimately, it’s about safely dosing Phase I participants, and effectively dosing Phase II and III participants. But what kinds of participants? With which compounds? And which endpoints or outcomes should we measure? These are just some of the strategic questions that precede every pre-clinical program. Without informed answers, time, money, and patient safety are all put at risk. In this session, William Copalu, PharmD, PhD, Vice President, Clinical Pharmacology and Translational Medicine, Certara, will present the intelligence and methods needed to get to the right answer.
Advancing Decision Making in Drug Discovery with D360
Safety from In Silico to In Vivo
Small molecule discovery projects need to minimise safety-related attrition. By using Quantitative Structure-Activity Relationship (QSAR) models, this can start at the beginning of the discovery phase when medicinal chemists are considering what compounds to make. As a project progresses and finds compounds of interest, in silico tools to assess safety using in vitro assay data can help project teams identify and design away from safety hazards. Finally, risk assessments made using data from regulatory safety studies on the candidate drug can be enhanced using in silico tools. Dr Chris Pollard will share Certara’s current and planned products designed to address each of these aspects of non-clinical safety.
During the conduct of non-clinical studies, researchers collect empirical data to further characterize a compound’s safety profile. But the volume and dimensionality of that data – thousands of data points across lab measures, histopathology findings, clinical observations, exposure measures, and more – can make the identification of safety signals challenging. Visualizing non-clinical study data within and across studies can help scientists extract intelligence from ongoing and completed nonclinical studies. Joyce Zandee, Vice President of Product Management, will demonstrate how SEND Explorer helps teams proceed to first-in-human dosing with more confidence and efficiently make data-driven decisions about compound safety.
11:30
Networking Break
12:15
First in Human Dose Optimization with SimCyp Discovery and PBPK Consulting
13:00
Networking Lunch
14:15
QSP in Pre-clinical Development
Now that PBPK has helped us define a safe range for dose, how can we gain confidence that our novel therapeutic or MOA will elicit the desired response? Of the safe dose levels, which are likely to show efficacy in our Phase II? What kind of dose-response relationship can we expect, and will it vary between populations?
These are just some of the many questions that QSP seeks to answer. In this session, a series of presentations by accomplished modelers will show us how.
Dr. Koep will share methods and findings from anti-FcRn-anti-albumin treatment simulations, targeting the neonatal Fc receptor to reduce levels of pathogenic immunoglobulin G antibodies.
Dr. Wagenhuber will present applications of virtual patients to drive decision making in translational research and development.
Dr. Vrohlings and Biswas will explore the QSP-based derivation of the starting dose for CDR404, a bispecific and bivalent T-cell engager antibody targeting MAGE-A4. They will showcase key preclinical data that informed the model development and discuss how this model has guided clinical development and starting dose selection.
14:45