January 31, 2017
Improving drug discovery: the Human-On-Chip project
In our sector it is well known that the process of drug development takes on average 10-15 years to be completed, and it costs over $1 billion to finally launch a successful drug onto the market. Around 60-80% of drug discovery projects are unsuccessful: many drugs fail once they enter the clinical stages of the drug development process.
 
These failures have multiple causes, a very important one being the unreliable extrapolation from in vitro and animal model results to humans. The inherent differences between cell-biology and organ level physiology is one of the key challenges of the drug development industry.

 
The concept of Organ-on-chip (OoC) and its evolution to Human-on-Chip (HoC) has been developed in an attempt to improve the translation of pre-clinical results to the clinic. OoC is a device composed of human-derived cells, cultured on a chip that systematically measure pharmacological responses. HoC is a platform that integrates several OoCs (with cells derived from various human organs: liver, gut, heart, lung and kidney) with the final objective of testing the most relevant organs simultaneously.
 
Intelligent Pharma attended the VIII Drug Discovery Network in Santiago de Compostela last November, where Dr. Danilo Tagle discussed the challenges his team at the National Institute of Health (NIH) face during the extrapolation of preclinical results into humans. Dr. Tagle explained how the HoC platform can improve the prediction of safety and efficacy of candidate therapeutics in humans, and their ambition to use the HoC platform for future clinical trials-on-chip.
 
The HoC platform has great potential but also has challenges; for example the management and interpretation of the enormous amount of data generated is not straightforward. December 2016’s editorial of Drug Discovery Today “Computational approaches for modeling and analysis of human-on-chip systems for drug testing and characterization” argues for the use of computational models in order to use the HoC platform to its fullest. Do you think that the HoC platform in combination with computational models will help to translate pre-clinical results to the clinic?

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