Personalized doesn’t equal exclusive – why we should rethink our understanding of personalized medical treatment

Over the last decade, the concept of PPM – precision and personalized medicine - has taken the biotech industry by storm, stemming from personalized diagnostics and custom medical devices (think custom-coated orthopedic or dental implants) to treatment plans in deadly age-related diseases such as various types of oncology.?

The VC industry caught up, too – biotech investors, including us at LongeVC, have committed significant amounts of liquidity into companies promising treatment or care “personalization” to wider groups of patients. These ventures typically build their narrative on improving the quality of care in various disease domains while keeping the needs and specifics of a particular patient at the center of clinical decision-making.?

These are incredible milestones in human health and longevity. Yet, when you see the word “personalized”, it is easy to assume this means “not for everyone.” This could not be further from the truth - personalized medicine is the future.

So what constitutes a personalized treatment? The traditional way of understanding personalized patient treatment is considering the needs, conditions, anamnesis, and specific traits of a particular patient in clinical decision-making. In other words, the patient, no matter which disease domain, should not be viewed as a generalized portrait of a “30-year-old woman” or “50-year-old man” but rather as an individual whose specific personal conditions and damage accumulated over the years of life is unique. And while being unique, it also generates a potentially unique response (or no response at all) to the generalized treatment protocols.?

At this point, one should raise a valid argument about the state of care. Healthcare providers shoulder an immense responsibility to attend to a patient’s needs, navigate them through a patient journey, and stay up to date on the best and most necessary diagnostic procedures. This is already quite a bit of patient care personalization that is (or should) be available to all. Of course, it would be unfair to say that all patients are treated by the same playbook. However, generally, they should be, as patient triage, diagnostic and treatment protocols are all based on the notion of maintaining a potentially high throughput of the healthcare system. In other words, to offer healthcare at scale, you should standardize procedures and protocols to the point where patients are viewed as units. These units should have, with a high statistical probability, roughly the same set of issues, at different degrees of severity, and respond to treatments in roughly the same manner. Here, we arrive at the basics of the healthcare system at scale – standardization allows us to provide reasonably efficient care to most patients, not all of them.

In many cases, there needs to be more time, with an average length of patient assessment by the healthcare provider being just a little over 10 minutes. We can, thus, call most modern healthcare systems non-personalized by design. At least in our understanding of the term.?

Our attempts to solve this are inefficient and often one-sided – there are countless digital health, AI-driven diagnostic companies, and other players trying to either introduce even more SOPs into an overloaded routine (think “giving a doctor another iPad type of solutions”) or simply struggling to integrate their solutions into already established protocols (in fact, AI-driven radiology has been the most successful here, yet still far from universal adoption). Maybe, one should then re-think the meaning of “personalized” and assume that it does not necessarily mean “spending more time on a patient” but rather, “a standardized treatment potentially efficient for everyone”??

While the claim above is, to some extent, provocative, let me illustrate it with a simple use case of oncology treatments. The choice is obvious – the disease burden is extremely high, and so is cancer’s uniqueness in every patient. An obvious priority for personalization. Yet, a patient with a freshly diagnosed Hodgkin’s lymphoma, under the premise of the standardized healthcare system, would be with a high likelihood of looking at a default chemo protocol - ABVD, with a chance of getting a combination treatment with radiation, which has proven to generate a response in a significant number of patients, becoming a standard of care. No two cancers, however, are the same. In fact, with some of the most heavily mutation-prone ones, such as melanoma, each case has the potential of presenting a unique combination of tumor mutations, potentially rendering any standardized therapies merely a matter of luck. Luckily, with personalization becoming one of the major turfs of innovation in oncology, companies are working on rapid treatment personalization options – a good example is Swiss Precomb Therapeutics , capable of rapidly growing patient tumor twin ex-vivo and testing possible treatment combination responses. Such approaches, however, are still mostly in early clinical validation stages, pending approval.?

Building upon the previous argument, and sticking to the PPM principle in oncology, what are the major hurdles preventing us from going personalized and acknowledging the uniqueness of every patient? I can offer a few:?

Hurdle 1: Disease Burden

There are simply too many patients and too few doctors to devote significant time and, sometimes, creative thinking to approach every case uniquely. This is especially true for CEE healthcare systems, overloaded and understaffed.

Hurdle 2: Findings into Actionable Regimen Changes

There’s a disconnect between finding options and transforming them into actionable treatment regimen changes. We are very often quite good at locating and listing the mutations a tumor has but have no clue of how to transform these findings into treatment corrections for a specific patient. Foundation Medicine’s personalized tumor sequencing is a great example of this unobvious, yet very acute issue: in my work I often encounter oncologists and get to talk about protocols, treatment options, and degrees of personalization. Foundation Medicine reports have, in many ways, pioneered the space of oncology diagnostics, providing a very comprehensive breakdown of tumor’s mutation burden in 6-week time from sample collection. A practitioner, however, will most likely understand 3% of all mutations provided in the Foundation’s report. So, more data does not equal more insights.?

Huddle 3: Poor availability of options in the market

For the most part, especially in underfunded healthcare systems, such as CEE, personalization is not available due to certain services not being reimbursed or offered whatsoever. Take Latvia as a prime example: state-funded NGS for oncology patients is vague and available only in very specific conditions, takes 8 weeks to perform, and offers very limited panel options. An average healthcare provider takes 10 minutes to attend to a case, treatment is only protocol (or rudimental) driven. Being a melanoma patient, you are lucky to get your BRAF results fast. New therapies, such as immune checkpoint inhibitors (e.g. anti-PD1), have only been around for a few years. Foundation’s report, although available, runs at a considerable expense for a patient and, for the most part, is not affordable to a wider population. All these bottlenecks are, unfortunately, not unique at all. Even companies such as Precomb still run very limited RnD collaborations with selected leading university hospitals.?

Personalized medicine is the future but it isn’t here yet. And yes, I would agree that the picture I’ve described here is grimmer than the rosy future the term personalized medicine paints. However, we have to be realistic in assessing the degree of personalization in current patient journeys and treatment protocols across various disease areas. The truth is, healthcare systems are by design not meant to spend a considerable amount of time with the patient. The future of personalized medicine then must lay elsewhere – in how we adopt treatments of universally high efficacy while maintaining an efficient system.

Excitingly, there do seem to be treatment regimens that have the potential to be “personalized for all.” CAR-T therapies have demonstrated efficacy across several oncology areas, and immune checkpoint inhibitors (pembrolizumab, nivolumab, and others) have been game-changing in lung cancers, melanomas, and several other aggressive oncological conditions. TIL-based approaches are promising in early clinics, and pioneering companies such as Epizyme or Turn Bio are pushing through their personalized epigenetic clinical programs. IL27 therapies show promise in non-small-cell lung cancers, as well as activation and recruitment of both innate and adaptive immune systems (see Surface Oncology for some exciting IL27-related work). And other disease areas have their pioneers too. Their promise shows the promise of personalized medicine - instead of resigning ourselves to the Herculean task of redesigning our inherently outdated healthcare systems and adopting to every patient, we can instead focus on providing universal availability of therapeutics, which will provide a universally higher efficacy rate. And VCs, to a large extent, should assume the responsibility of accelerating these solutions to market.?