Investing in Function Oncology | Andreessen Horowitz

“The power of tailored therapeutics is that we say more clearly to payers, providers and patients, ‘this medicine isn’t for everyone, but it’s for you.’ That’s very powerful.” —John C. Lechleiter, Ph.D., former chairman, president and CEO, Eli Lilly and Company, in comments published by The Personalized Medicine Coalition (PMC)

The precision medicine paradigm is powerful: for cancer patients and for the entire oncology ecosystem. Since the 1990s, the FDA has approved more than 50 targeted (‘tailored’ or ‘genome-informed’) oncology drugs for clinical use and they have been put into practice with increasing payer coverage of genomic profiling of the tumor This wave of targeted therapy approvals began with high-impact drugs such as trastuzumab in 1998 for HER2+ breast cancer, imatinib in 2001 for chronic myeloid leukemia, and erlotinib in 2004 for advanced lung cancer mutant EGFR, and continues through 2023 with a number of recent approvals. in the first quarter of this year alone, in indications ranging from lymphoma to colorectal cancer to subtypes of endometrial cancer (adjustment repair deficiency or dMMR). The pace of therapeutic innovation has been impressive.

The patient <> therapy matching problem in oncology

However, patients and their care teams also face several harsh realities. The average response rate for all new cancer therapies approved over the past two decades is only 41%, with only 25% of all cancer patients eligible for “genome-informed” therapies based on alterations of the DNA of their tumors and the percentage. of all cancer patients who will actually benefit from an approved genome-based therapy is still likely to be less than 15%.

In practice, off-label use continues to grow and the indications for existing targeted therapies continue to expand. But for most cancer patients, we have no way of knowing whether they will respond to a particular therapy… until after they actually receive the therapy.

For most cancer patients, we have no way of knowing if they will respond to a particular therapy…until after they actually receive the therapy.

Put yourself in the shoes of an advanced cancer patient today. You may have heard that many new cancer drugs have been developed, which is great news, but you have a limited number of shots at the goal and you only care about the drugs that will actually work for you. To find out if certain drugs might work for you, your oncologist can provide a comprehensive genetic profile (CGP) of your tumor, but there is a >75% chance that nothing possible for you will be found on these tests. Let’s say you are one of the 3 out of 4 patients in whom DNA sequencing does not indicate any specific therapy options. You’re left wondering: Does my cancer also have an Achilles heel? Could one of these newly approved targeted cancer drugs be functional against my tumor? How could we find out, quickly and accurately, so that I don’t have to waste time trying therapies that don’t work?

This is a conundrum for the wider oncology community as well. For example, medical oncologists often choose between two or more treatment options that may have similar supporting evidence on a population scale, but may have very different efficacy among individual patients. Payers, or insurance companies, often bear the cost of therapies that must be empirically tested over several months, only to learn later that the patient may have received no benefit, or worse, experienced toxicities ( expensive). And for biopharmaceutical companies searching for new cancer drugs, stratifying patients by their likelihood of response is a clinical development game changer, reducing the time and cost to bring new therapies to patients.

In summary, from all perspectives, we still have a problem of patient <> therapy matching in oncology. And this “problem” is only getting worse as the arsenal of targeted therapy continues to grow. What if it could become a massive opportunity?

We still have a vexing patient <> therapy matching problem in oncology.

Building the data platform for a functional future

If translational oncology research has taught us anything over the past few decades, it’s that cancer is creative. Cancer cells can find ways to co-opt normal function and exploit the pathways in so many different ways to their advantage. And as we have learned, these mechanisms are not always encoded in DNA changes; they can manifest in epigenetic changes, changes at the RNA level, splicing changes, protein conformational changes, and the list goes on. As such, while it is disappointing that tumor DNA sequencing provides useful clarity in only 1 in 4 patients, it is not fundamentally surprising.

And if we could investigate the reality gene function (compared to the gene sequence alone) of different targets in a patient’s tumor cells? What if we could find the functional Achilles heel(s) of each patient’s cancer, before prescribing therapy? While many teams have built several ex vivo (outside the body) diagnostic assays in which tumor cells are exposed to a panel of drugs, none are used in routine practice today and few have offered mechanistic insight into the precise functional pathways on which a patient’s tumor may depend.

Enter the Oncology Function. The team is building the first real-world functional oncology data platform, a growing and continuously evolving dataset of cancer cells from primary patients that have been extensively profiled to identify patient-specific functional dependencies—genes , proteins and pathways to which patients. Individual tumors are addicted. If we could learn this information about each patient’s cancer, at the right time in their clinical journey, the emerging opportunities are endless. The “problem” of too many available targeted therapies suddenly becomes an opportunity: functional profiling could drive personalized therapy selection in the clinic, smart repurposing, and off-label use of many already approved drugs and smarter preclinical and clinical development of new oncology drugs in our industry.

The team is building the first real-world functional oncology data platform.

CRISPR strikes again

So how does Function Oncology learn the functional dependencies of a patient’s tumor? For starters, they’re taking advantage of CRISPR tools in a very creative way. CRISPR technology has taken the bio world and even popular science by storm over the past decade, spawning a wave of exciting programmable medicine companies, the creation of numerous biotech platform companies, and even a Nobel Prize.

But as many in academia and biopharma know, some of the most transformative impacts of CRISPR’s capabilities have actually been felt in preclinical research: the ability to disrupt (eliminate, dampen, or even turn on) the function of a single gene in cells with a known genetic background is a game changer, because it can closely mimic (“phenocopy”) what a therapeutic medicine might try to do. Functional CRISPR genomic screens (perturbations across a large panel of genes to identify new targets or gene modifiers) are now a cutting-edge capability at many modern biotech companies, but Function Oncology is taking it a few steps further : in primary patient cancer cells, for real-world clinical and diagnostic use. As the founders of Function Oncology explained to me, sometimes CRISPR is the therapy, but here, maybe CRISPR can help us choose the right therapy for the right patients. We found this vision inspiring, a new vision of a “biologically engineered future.”

The FxOnc team: twins, technologists, tirelessly focused on the patient

A former Flatiron / Foundation Medicine colleague, Alex Parker, first introduced us to the founders of Function Oncology (FxOnc). He mentioned the team with a “…I have a feeling you’ll really enjoy chatting with them.” As our smiles below suggest (a reminder of the day we agreed to work together!), this turned out to be so true.

Srinath and Hari, both MD/PhD medical scientists, are sort of lifelong collaborators – twin brothers! – and the three founders Srinath, Hari and Christian had been working together for many years as researchers and leaders in the Genomics Institute of Novartis Research Foundation (GNF). ) in San Diego before starting Function Oncology. They bring a unique combination of familiarity and expertise in clinical medicine, basic science, and therapeutic research and development. Like many of our top startup teams, they are brash but also rigorous, ambitious and relentlessly patient-focused.

Here’s to massively multiplying the number of cancer patients to whom our therapies can offer hope. We are honored to partner with the Function Oncology team in their mission to advance a new paradigm of personalized oncology.

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