Simple reliable assays render drug that are clinically useful.
We all recall the succesful attempt of James Cook to discover the drug against scurvy. He basically conducted the first placebo-controlled clinical study known to humanity.
Discovery of synthetic and semi-synthetic antibiotics wouldn't be possible without the predictive nature vitro bacteria cultivation. In this way human being realized the potential of drug testing without jumping straight into clinical trials.
Unfortunately, this approached cannot be applied to all disease areas. Oncological drugs for many years already has the worst success rate in clinical studies. Translation from conventional cell and animal models of cancer diseases is still on the lowest level in drug discovery.
Conventional immortalized cell lines, despite being highly scalable, fail to represent the human disease. Perhaps, genomic instability of those during prolonged cultivation alters the response of the cell to applied drug. Another problem is that real human tissue has much higher complexity than monoclonal cell culture.
Modern organoid, spheroid and organ-on-chip cultures attempt to resolve those issues.
Preci is a platform that wants to unite those systems and use only the most relevant onve (hystologically and genetically) to bring more representative drug discovery. Additionally it has the capacity to derive those cell models from the population of donors (10s and 100s for some diseases).
Every single patient needs to be represented in vitro to accomplish unbiased conlusions. No technical solution offers the generalized approach to model all cancer cases. Our case-to-case approach and thorough predictivity analysis, involving real patient history can achieve that.