“Drug Combinations and Off-Label Drugs”

papers with combination dosing strategies provided in the report. ●We will provide report reviews on request. Brian McCloskey asked about on-off cycling through drugs, an idea promoted by Dr. Bob Gatenby. Saed Sayad and Dr. John Laird observed that our guidelines, which push to maximum tolerated doses, are driving cancers to resistance – a flawed strategy.

Saed Sayad presented a hypothesis that RCC1 could be a biomarker to predict cancer recurrence after prostate surgery. Requests ●Do you have any feedback on drug combinations and off-label uses of approved drugs?

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“Drug Combinations and Off-Label Drugs” (Ally Perlina) [#7] — The information and opinions expressed on this website or platform, or during discussions and presentations (both verbal and written) are not intended as health care recommendations or medical advice by Cancer Patient Lab/Prostate Cancer Lab, its principals, presenters, participants, or representatives for any medical treatment, product, or course of action.

You should always consult a doctor about your specific situation before pursuing any health care program, treatment, product or other course of action that might affect your health. Meeting Transcript Brad Power: We are going to start today with feedback on Ally Perlina's presentation about CureMatch.

For those who don’t recall Ally’s presentation, the CureMatch approach has two key features: combinations of drugs and off-label use of approved drugs, and there was some conversation about people being interested in clinical trials.

Brian McCloskey: As Brad mentioned, we were able to circulate Ally’s presentation about the CureMatch report based on my profile and get comments from some of my oncologists, Emma Shtivelman, who's on the call today, and Peter Kuhn. I grabbed a few snippets of feedback that came in and we can take these one by one.

“Drug Combinations and Off-Label Drugs” (Ally Perlina) [#7] Brian McCloskey: Ally, I'd love to get your feedback in terms of whether or not these are issues that you have come across, or if these are new, and what your thoughts are in terms of how to address them. The first came in from Tanya Dorff, who is an oncologist at the City of Hope.

She liked looking at the mutational analysis, but she questioned whether or not there was a clinical advantage to using an all-in strategy or looking at these agents sequentially.

s are in terms of how to address them. The first came in from Tanya Dorff, who is an oncologist at the City of Hope. She liked looking at the mutational analysis, but she questioned whether or not there was a clinical advantage to using an all-in strategy or looking at these agents sequentially. Ally Perlina: That's surprising to hear from somebody at City of Hope.

We don't usually need to convince anybody when we deliver our reports that it's better to cover as many bases as possible of what's driving a patient's cancer.

In the many dozens, if not over a hundred, reports that we delivered where I was participating and reviewing, I haven't once met an oncologist who said, “why would we want to target all the mutations that are driving the patient's cancer as opposed to one at a time?” I think that's old age thinking that you can just target one at a time.

The evidence is pretty clear that when the drivers are left untargeted, they most often promote the next set of clonal expansion of those cancer cells that have the drivers that are not targeted. The motivation to try to target as many of the markers at once as possible seems well accepted.

We have evidence that patients that are partially matched or have a lot of mutations left unmatched don't do as well in terms of progression-free-survival and overall survival.

“Drug Combinations and Off-Label Drugs” (Ally Perlina) [#7] several study results showing that it's the degree of matching that actually matters. It's like how many birds can you shoot with as few stones as possible, which is why we have the score. Since the beginning of the company in 2015 by Dr.

Razelle Kurzrock, we've had clinical evidence showing that no matter what the cancer is, no matter what the data set is, the higher the matching, the better the outcomes, and the worse the matching, the worse the outcomes. Nobody wants to turn a blind eye on a cancer driver and leave it untargeted. The industry may struggle to deliver multiple drugs in an affordable way.

It’s not the standard way to get three drugs at a time. We still see a lot of physicians will opt for two different drugs, and see how the patient does. And then they will add another one. Or if a patient is already on a drug and responding, they'll keep their patient on the treatment because they're seemingly doing okay.

Our recommendations include immunotherapy, chemotherapy, and all kinds of targeted therapies that are approved. I shared a slide with evidence, and we're going to be publishing more with even bigger data sets with the latest algorithms that show that the higher the score, the more markers you cover, the better patients do.

Brian McCloskey: You mentioned the expense of off-label drugs, which was another issue that Tanya mentioned. Do you have any data that compares the cost of the combinatorial approach with off-label drugs versus standard care monotherapies?

ore, the more markers you cover, the better patients do. Brian McCloskey: You mentioned the expense of off-label drugs, which was another issue that Tanya mentioned. Do you have any data that compares the cost of the combinatorial approach with off-label drugs versus standard care monotherapies? Ally Perlina: I'll send a link to an independent evaluation that priced out our recommendations.

There are choices and options that follow the molecular rationale. This will help make a case for a physician to get it covered or partially covered. Under our targeting description there are always alternative drugs that have the same therapy type and the same targeting mechanism.

With these alternatives the score can be almost the same or exactly the same, but one treatment would cost a lot more versus the other one. We have this model where we include the molecular matching and clinical value with the financial feasibility – getting the highest score for the least money. Plus, when combining multiple drugs physicians often opt to start with much lower dosages, e.g.

, one third on a three-drug combination, or a half dose on a two-drug combination, then titrate up as much as makes sense. We have a calculator, which can be used to estimate the most impact with the smallest price of the drugs.

Finally, we show that having three-drug and two-drug combinations is a lot less costly and less of a burden on the patient, the doctor, and the medical system, than having one drug that has no molecular basis.

Cancer centers have drug acquisition specialists, who are trained to make appeals to compel drug coverage and reimbursement, and having this molecular rationale in the report to attach helps them. Brian McCloskey: You talked about lowering the dosage when you combine several drugs. Have you looked at cycling on and off a therapy, e.g.

, on for three months, take a holiday for three months, get back on for three months? Do you have any data that supports that? The reason I'm asking is that we had a really interesting conversation with Bob Gatenby yesterday. He is an evolutionary biologist at the Moffitt Cancer Center in Florida. He has spoken and written a fair bit about adaptive therapy.

When you mention going for lower dosage, which makes sense when you're doing drug combinations, it raised this question in my mind of how he approaches it, where he lowers dosage. He doesn't go for the kill shot.

“Drug Combinations and Off-Label Drugs” (Ally Perlina) [#7] Ally Perlina: No, we don't have any evidence that would support it. Maybe this is something new and emerging, but we only have evidence to show that you should target more markers at once. There's no other data. Everything we put in our system is extremely well curated, and it's all under the guidance of Dr. Razelle Kurzrock.

It's not like there is just some independent AI that just comes up with some serious predictions.