High-Content Imaging Technology for Prediction of Toxicity
Assess the application of HCS toxicology assessment for your drug-discovery program, Dr. Katya Tsaioun, Chief Scientific Officer at Cyprotex talks to Pharma IQ.
Pharma IQ: There are challenges around predicting organ toxicity using simple mechanistic endpoints such as Mito Tox and oxidative stress, how can this be improved?
Katya Tsaioun: Both systemic and organ toxicity are frequently a combination of multiple mechanisms, so if mitochondrial toxicity, phospholipidosis or oxidative stress models are used, they will detect only toxicities associated with these mechanisms. Measuring multiple mechanisms of toxicity in the same cell population such as with HCS imaging technology has been demonstrated to be a powerful tool in de-risking drug discovery programs that improves sensitivity and specificity of predictions.
Pharma IQ: What are the most recent tools available for the reduction of adverse effects and the successful prediction of long-term toxicity?
Katya Tsaioun: Human origin cells such as primary cells and stem cells-derived models are available now to use in lead optimization and preclinical candidates’ selection stages to reduce adverse events in late stage preclinical, clinical development and on the market. 3-D cell models such as sandwich hepatocytes and co-cultures supporting long term cultures are technologies that are currently under intense investigation and are promising models for chronic toxicity prediction.The timing for the conference is perfect to bring together the industry and government leaders such as Pfizer and EPA and have a discussion about the validation of the models and how they are used by all parties.
Pharma IQ: Why in your opinion is it important to have this 1st Predictive Toxicology event in the US now and what are you hoping to gain from the conference?
Katya Tsaioun: The field of toxicology is undergoing a rapid transformation in the US. Five to ten years ago it was unthinkable to hear regulatory bodies (FDA, EPA) considering not only putting in vitro assays in the regulatory path, but replacing animal models with more appropriate human toxicity-relevant models, which has now become more commonplace.
At the last SOT meeting it was obvious by the number of sessions devoted to predictive, in vitro and in silico models that the society is taking this field seriously. The presenters are now heavily skewing into industry as technologies are moving from academia into main stream industry and are being validated and used in conjunction with ADME to de-risk drug discovery compounds and agrichemicals. So the timing for the conference is perfect to bring together the industry and government leaders such as Pfizer and EPA and have a discussion about the validation of the models and how they are used by all parties.
Pharma IQ:You will be delivering a session on High Content Screening for Prediction of Toxicity – can you share with our audience what this session will focus on?
Katya Tsaioun: This workshop will review different industry approaches for using high-content imaging technology for predicting toxicity in potential drug candidates. This technology is widely accepted in the pharmaceutical industry as a valuable tool that is poised to reduce attrition in the drug development process and to significantly accelerate and improve the cost-effectiveness of the process from “hit-to-lead” and lead optimization.
Basics of HCS will be covered that include principles, end points, cell models and equipment. Subsequently, background and rationale for using HCS for systemic and organ toxicity prediction will be presented, illustrated by validation studies. Finally, state-of-the-art information on cell models will be discussed (cell lines, primary cells, stem cells-derived models, their advantages, disadvantages).
Interview conducted by Niamh Madigan.
|Have Your Say|
Rate this feature and give us your feedback in the comments section below
Please note that we do all we can to ensure accuracy within the translation to word of audio interviews but that errors may still understandably occur in some cases. If you believe that a serious inaccuracy has been made within the text, please contact firstname.lastname@example.org