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Prostate Cancer Lab #18: Drug Testing and AI/ML for Clinical Decision Support

Meeting Summary

“We get the fresh sample, we process it, we use what we need for drug testing, and we freeze them down. If we need to go back and test combinations, we’re throwing those out fresh and testing within a few days.” – Diana Azzam

Presentation Highlights

Noah Berlow, PhD, CTO, First Ascent Biomedical, and Diana Azzam, PhD, Assistant Professor at Florida International University, led a discussion on their approach to functional drug testing and using AI/ML to guide complex treatment decisions for advanced cancer patients. Diana’s expertise is in functional precision medicine, and Noah’s is in AI/ML and bioinformatics. Together they have put together a pipeline that takes in fresh patient tissue and turns out treatment recommendations in two weeks. They use Diana’s functional drug testing protocols and send out some of the tumor tissue for DNA and RNA sequencing, then put the test results into Noah’s matching engine to report treatment options to patients.

Diana shared several examples of advanced cancer patients who had failed standard treatments and were desperate for treatment options, which were discovered by the drug testing she ran. Many of the treatment options were unexpected. Some were chemotherapy drugs that the patient had already seen and were assumed would be ineffective. One drug was an approved drug – for asthma. The drugs were delivered in combinations. All extended “progression free survival”, and one patient experienced a particularly durable response. These patients had urgent needs since they had failed their previous lines of treatment, and the analysis was completed within two weeks to give the patients timely treatment recommendations.

Noah described his work in integrating and interpreting the inputs of functional drug testing and sequencing data for individual patients with information about the drugs and their real world mechanisms to derive a personalized “tumor circuit” – a holistic view of tumor drivers and weaknesses to find the best combination of drugs for a patient. He shared his research in applying this analysis in mice, where he was able to find personalized drug combinations that performed better than a control or the individual drugs. He also showed how the same analysis that they built to find individualized combinations for patients can be applied to discover better biomarkers.

Discussion Highlights

We support administering multiple drugs together, instead of single drugs one-by-one, because you give the cancer cells the chance to adjust to every chemical you throw at them.

Noah Berlow: In many ways I’m in agreement. Some of the other work that I’ve done has been on showing the difference between sequential combinations or simultaneous combinations using the AI to find a combination and then testing that ex vivo on a couple of cell models derived from the same type of cancer, showing the combination can essentially stop tumor regrowth. But at the same time, we’re showing in a practical setting, when you give the drugs at the same time, the effect is that the cancer cells go away and don’t come back. Which of course is the key end goal.

We have heard concerns about toxicity from treating physicians regarding the kinds of drug combinations you are recommending. How did you overcome those concerns?

Diane Azzam: I have not really seen toxicity concerns because our patients haven’t had other options. We look at the drugs’ concentrations in the blood and use Cmax. (Cmax is the highest concentration of a drug in the blood after a dose is given.) In the case of the osteosarcoma patient, they administered the drugs in a rapid sequence – a few weeks. In the case of the rhabdomyosarcoma patient, we had seen in functional testing that one of the drugs (vincristine) was stronger as a single agent, so they administered that first, then the other two in a rapid sequence.

You’re working off fresh tissue. Can you run one functional test, then come up with a new hypothesis, and run functional testing again without getting a new biopsy? Is the tissue still viable for testing after 48 hours?

Diana Azzam: We get a second shot. That’s what happened in all the cases, because we get the fresh sample, we process it, we use what we need for drug testing, and we freeze them down. If we need to go back and test combinations, we’re throwing those out fresh and testing within a few days. It’s very helpful because sometimes doctors look at the single agent data, and say, “I want you to go back and test these combinations.”, and that’s what we’ve done. It’s been very helpful for the doctor.

Meeting Recording

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