Top: Zofia Bielecka, Barira Islam, Chris Pollard.
Bottom: Hiba Khalidi, Will Redfern, Emily Jo.

What is SIMCYP-Certara’s main focus?
Providing in silico solutions to speed-up drug discovery and development: basically, getting safer, more effective drugs to patients faster.  By ‘in silico’ we mean data handling, analysis and visualization, modelling & simulation.  For example, our tools facilitate and  improve decision making in drug discovery, safety and DMPK (drug metabolism and pharmacokinetics).  They reduce the number of animals used in the preclinical phase, and can substitute for certain expensive, time-consuming clinical trials (for example, predicting drug-drug interactions).

How has participating in TransQST impacted your company?
Our modelling work within the various work packages in TransQST have provided an intellectual challenge to our participating scientists.  SIMCYP-Certara participants in TransQST have co-authored high quality publications.  It has also enabled us to remain abreast of pharma industry and regulatory trends and strategies.  In addition it has provided excellent networking opportunities, with potential collaborative partnerships beyond the duration of the TransQST consortium.

What challenges has SIMCYP-Certara faced across the project? What are your main achievements in TransQST?
This was an ambitious project tackling drug safety across various organ systems, each under a separate work package.  We developed/co-developed useful and usable physiologically-based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) models across different work packages, including kidney, liver and gastrointestinal tract, and also undertook PBPK modelling to estimate intracellular cardiac concentrations of cardiotoxic drugs.  One of the challenges (even pre-pandemic) was waiting for data from the EFPIA partners to build/test the models, which makes it difficult to plan and allocate resources to the project far ahead.

Which TransQST outcome/s would you highlight? Why?
The Quantitative Systems Toxicology (QST) model of drug-induced liver injury (DILI), which we were heavily involved with, and the toxicogenomics TXG-MAPr tool, which was developed by the University of Leiden.  Both these models are currently working with in vivo readouts.  However, in the long-term, we will need to replace animal studies with a combination of in vitro and in silico approaches, so this is a first step.  Any replacement of repeat-dose animal toxicology studies is almost certain to include these two approaches.  Currently the TXG-MAPr tool is focused on DILI, but over time will address other organ toxicities.  This tool provides a statistically robust analysis and visualisation of gene up- and downregulation in response to the toxic effects of drugs at different dose levels. 

What do you believe is the main contribution of TransQST in the field ?
TransQST has ensured another step has been taken in the direction of removing scepticism around modelling and simulation in drug safety assessment, and in increasing its credibility.  However, there is still a long way to go until there is more widespread acceptance of modelling and simulation in toxicology and safety pharmacology within the pharma industry and regulatory agencies, and even further until it is fully embraced.  Developing in silico strategies to understand the risk of toxicity in humans is an important step in eventually being able to replace/eliminate pre-clinical toxicity testing of potential new drugs in animals.