The virtual clinc: Optimata in pilot study with Eli Lilly

Eli Lilly & Co. pilot study utilizes Optimata’s “virtual patient” technology to assist in the development of clinical trials for a novel anti-cancer cytotoxic compound.

Chris Anderson
Register for free to listen to this article
Listen with Speechify
RAMAT GAN, Israel—In late March, Optimata Ltd. announced that it had completed the first phase of a pilot study with Eli Lilly & Co. that utilizes Optimata's "virtual patient" technology to assist in the development of clinical trials for a novel anti-cancer cytotoxic compound.
In the pilot study, Optimata researchers are using the company's proprietary virtual cancer patient software to evaluate data from Lilly in an effort to provide a more targeted and effective clinical development program using in-silico predictions of the expected human response to the compound in varying doses.
"Pharma companies have a big problem with Phase I trials for cancer," says Guy Malchi, president of Optimata. "It is very difficult to recruit patients because the starting dose is so low and they escalate that too slowly, with only a small portion showing any improvement. There is also the humanistic concern that by entering Phase I studies the patient could be delaying other therapies."
Optimata's virtual patient technology may be one way to get over these two problems, Malchi notes, by predicting which dosages of a drug will have the greatest effect on a patient population and what the predicted outcomes will be. The pilot study at Lilly directly addressed this potential by providing Optimata with pre-clinical data on a promising cytotoxic compound and having the software predict outcomes based on dosage levels.
"Lilly already had the data from the Phase I trial and hid it from us to see how accurate our virtual patient technology was at predicting outcomes," says Malchi. "It was the strength of our results that allowed us to announce that we have successfully completed the first phase of the study."
But the technology at work is not just applicable to clinical trial design. One potential use of Optimata's virtual cancer patient predictive technology is also to provide individualized patient models that can be used to optimize cancer treatments on a case by case basis. To this end, Optimata is also involved in breast cancer bio-simulation clinical trials with Nottingham City Hospital in England and Israel's Soroka University Medical Center.
"At the moment, we want to validate the (virtual cancer patient) program using real patient data retrospectively," says Dr. Stephen Chan of the department of clinical oncology at Nottingham City Hospital. "Once we've done that, we will be able to use the program to prove that by individualizing the treatment using the virtual patient concept and program, we can improve and make a tremendous impact on the treatment of our patients."
Through continuing studies like Dr. Chan's and the one with Lilly, Optimata also can continually improve the predictive accuracy of its product from the additional data it generates in this work.
Having passed the first hurdle with Lilly, Malchi says Optimata now turns its attention to creating an interactive clinical trial design. "Our hope and expectation is that once we complete the pilot study, that they will turn to us to support their Phase II design," he notes.
While working with major pharma companies such as Lilly is vitally important to the validation of Optimata's technology and its next stage of growth, the company anticipates that its technology in the coming years will increasingly be used by smaller drug discovery and biotech companies. "A company that has fewer assets and a few compounds in  the pipeline could benefit from our trials design and once we are more established we see great potential for outlicensing deals with these kinds of companies," Malchi notes.

Chris Anderson

Subscribe to Newsletter
Subscribe to our eNewsletters

Stay connected with all of the latest from Drug Discovery News.

September 2023 issue front cover

Latest Issue  

• Volume 19 • Issue 8 • September 2023

September 2023

September 2023 Issue