Finding the Right Tumor Fit for a Platform Technology

Platform technologies, product engines that can generate novel drug candidates or identify new drug targets, are popular these days in the oncology space. That’s not a complete surprise given that most of the “easy” validated drug targets accessible to traditional small molecules and antibody approaches have been mined. The list of top “criminal” genes in cancer contains plenty of fugitives that have escaped from traditional pharmaceutical approaches. Even more so, there are many more targets in the tumor outlaw organ like immune cells, myeloid cells (corrupted policemen) or other constituents of the tumor micro-environment that are waiting to be captured. This calls for bounty hunting biotechs that develop platform technologies with a potential to capture such difficult drug targets. Or conversely, CIA-type of biotechs with platforms that can identify novel criminal drug targets or find critical nodes/dependencies in criminal networks, a concept known in our industry as synthetic lethality. An attractive aspect of platform technologies is that they can go after multiple different targets, thereby mitigating the risk of failure in a particular program. Furthermore, platform companies can potentially generate more value earlier than asset-centric companies. For example, companies like F-Star and more recently Teneobio successfully used business models whereby platform-derived programs were co-developed with pharma partners in standalone subsidiaries, alongside an option to acquire those subsidiaries at a specific milestone with pre-negotiated deal economics. This model creates a sort of evergreen drug discovery biotech that enable multiple exits.

Platform technologies have the potential to solve many problems. However, start-ups have limited resources and cannot try to monetize each and every application of the platform. In the earliest days of company-building, founders are typically focused on optimizing and patenting the technology platform and understanding what works and what not, which can understandably delay them prioritizing and choosing which specific diseases to pursue. Given that oncology is one of the most competitive fields in life sciences, finding the best possible match between the platform and a particular tumor indication, or platform-tumor fit (PTF), is essential to success. The value of a platform company will only become apparent when its technology generates disease-transformative products with the value proportionally increasing as such products progress through the drug development stages.

Given that there are more than 100 tumor types and every platform and company is unique, finding that perfect platform-disease fit is not easy. With this article I provide a framework that hopefully helps in evaluating potential platform-disease fits.

1. The platform’s differentiative edge

The first thing to do in narrowing down the rich amount of options that you have with your platform technology, is to define what you can truly uniquely do. It’s not enough to solve a problem, you have to define a problem that only you can solve and not the others. For example, I previously managed Sapreme Technologies, a company developing a technology that liberates cargo from the endosomes. We spent the initial years to understand what types of cargo could and could not be shuttled across the endosomes. We focused our R&D programs on those types of cargo that could not be adequately delivered with current and competing technologies.

In another example, you could be focusing the platform on accessing high value drug targets that are currently undruggable. Your platform might be useful in targeting the KRAS oncoprotein that comes in many different mutant forms and is very high on the “most-wanted” list of pharma. If your platform has an advantage in accessing these high-value targets, this can be an interesting opportunity. In those cases, you will want to go for those KRAS mutants that cannot be drugged now and in the future with small molecules or competing platforms like PROTAC.

If you are developing a drug target discovery platform, it is best to go for pathways that cannot be inhibited by current drugs on the market, such as for example those controlled by tumor suppressor genes or transcription factors. You could also think about tumors types where there is an unclarity around the key oncogenic drivers or those tumors that generally have limited treatment options.

Spend some time thinking what problem(s) you can specifically solve with your platform and build some data supporting this if you have not done so already. Be rigorous about whether your technology platform has an unique edge and seek conformation from key opinion leaders (KOLs) that are willing to provide a truly honest opinion. Instead of going out to investors and pharma with a technology platform that does not stand out in the crowd, it is better to develop the technology until a point it has reached the right level of innovation. It is much harder to come back to investors and pharma if they have been underwhelmed in your first meeting with them.

Your next steps are to evaluate the possible tumor types where the platform could fit. For most tumor types, oncologists can choose from a multitude of treatments that are given as single agent therapies but more commonly as combination treatments. When tumors become resistant, patients progress to the next treatment line that consists of other therapeutic options. For some tumor types like breast cancer there are many treatment lines. The choice for a particular treatment depends on many variables, i.e. the stage of the tumor (risk profile), availability of genetic biomarkers that confer sensitivity to certain anticancer drugs, patient condition and patient’s preference. It is important to be precise about the treatment line where your platform-enabled drug could fit in, the so called product label. Good starting points are the treatment guidelines on individual tumor types that are provided by the National Comprehensive Cancer Network (NCCN) and the European Society for Medical Oncology (ESMO).

The framework below provides a means to evaluate scientific/clinical feasibility and commercial attractiveness. Within each of these axes there are several key factors to consider and for each, you can assign a low, mid, or high scoring that maps to how best to think about prioritization for a particular factor (the higher the better). You will find that there won’t be any perfect fits but that each option will have its pro’s and con’s.

2. Scientific and clinical feasibility

Determining scientific and clinical feasibility is about thinking which tumor treatment lines you could transform with reasonably good confidence. It’s about finding the right balance between an indication where you will have the most impact and the development risk is acceptable.

Target Validation

On the scientific side, you should ideally go for high value targets that have a strong genetic link and demonstrated causal relationship with a particular tumor type. Pharma (and so are VCs) tends to be quite conservative with new targets that have not been analyzed in meaningful numbers of patient-derived tumor samples and validated in functional experiments in animal models. Exceptions may be novel targets that convincingly perturb validated cancer pathways that are currently undruggable or areas where there is an heated interest in novel targets, such as immune-oncology. You should be mindful however that the window of opportunity to benefit from hype is not very long in life sciences, so timing is key. You don’t want to embark on a drug development program in an area that is on its way out. This can be learned by speaking with industry experts and monitoring pharma and VC activity.

Drug Modality Risk

Pharma is quite conservative when it comes to drug modalities and will predominantly stick to drug modalities that they are experienced working with. You need to be aware of this when you are considering to develop entirely novel drug modalities that are not yet adopted by pharma. Antibody–drug conjugates (ADCs) can serve as an example. When the target is not validated and the antibody, payload and linker technology all have not been tested in patients, there are significant risks. In the ADC field, a novel linker technology on its own can be sufficient to transform a disease outcome, as we have seen with Daiichi’s Enhertu (fam-trastuzumab) for advanced HER2-positive breast cancer, and will be more palatable to acquirers. If you do work with an entirely novel drug modality, don’t use that to go for novel unvalidated targets as you would essentially be doubling down on risk. Some drug modalities are also inherently less risky to develop. Antibodies for example improve the odds of success given their strong target selectivity, thereby reducing the chance of off-target effects, and with their long blood circulation permitting prolonged target engagement.

IP Dependency

When thinking over the drug modality that you want to be developing, there are also certain IP considerations to be looked into. Using the ADC example above again, you would need to know which parts of the product you can freely use without infringing a third party’s patents. You might reach the conclusion you would need to license a third party’s IP. In these cases, it is important to assess the likelihood that such a third party would grant you a license. You may have identified a way to reverse engineer around a third party’s IP portfolio but that’s a risky strategy, particularly if these are well-funded competitors. Even though you might have rightfully patented around their IP estate, they may sue you anyway, knowing that you wouldn’t be able to deal with the cost and time burden of a patent infringement lawsuit.

Disease Tractability and Quality of the Animal Models

Oncology is one of the toughest disease areas to develop drugs in, but some tumor types are more difficult than others. Pancreatic cancer and glioblastoma for example are infamously known as a graveyard indications. Conversely, liquid tumors are generally less risky given that these tumors are genetically more homogeneous and easier to access than solid tumors. Unsurprisingly however, you can expect more competition in blood cancers. Be certain to speak to a number of KOLs that are specialized in certain tumor types that have caught your attention to get a sense of the level of drug development failures and the reasons, and importantly, whether your platform-enabled product is likely to overcome these challenges. You will also want to know whether good predictive models are available for the indication. The larger conferences are good sources to identify the preclinical workhorses that are being used by industry. Another strategy is to query established CROs, these often have catalogues of genetically annotated oncology models in which standard of care treatments have been tested. Ideally you want to use a model that is aligned with the product label you are thinking of. For example, if you are considering to develop a product for non-small cell lung cancer patients progressing on EGFRi, then you want to look for lung cancer models resistant to prevailing EGFR inhibitors. In these competitive markets, you need to challenge products in the toughest cancer models in order to convince investors and pharma.

Ease of Clinical Development Execution

Critical parameters that you want to study in detail here are how long it takes to complete a trials in the tumor you are considering. Key determinants are how fast you can enroll patients in your trial and how fast these patients progress to a certain regulatory acceptable endpoint. The speed of accrual is determined mainly by the size of the patient population and the amount of competitors fishing in the same pool of patients. Some data providers track the accrual rates for tumor indications, which can be a good source to estimate trial timelines. Another strategy is to ask clinical CROs, though they might give you a more biased and optimistic view. Some tumors like prostate cancers for instance are relatively slow growing and it can therefore take some time before a sufficient number of patients have progressed to the canonical clinical endpoint. In some cases, particular endpoints used in the past may no longer be accepted by regulators. There can also be a discrepancy between what regulators would like to see to approve a product versus what convinces the oncologists that would be prescribing your drug. By talking to KOLs in various geographies and examining the latest treatment guidelines you can get clarity on these topics and furthermore also get a sense of the robustness of an indication. For example, the treatment guidelines of renal cancer have been adjusted significantly in a time frame of less than two years and will likely change again soon. Indications that are a moving target can turn into nightmares as there may be unclarity about the comparator arm and key patient population characteristics may be changed by these new treatments (for example fitness, tumor heterogeneity). Of final note, as discussed above, what will greatly facilitate drug development and improve the odds of the success is a biomarker to select patients that are likely to respond to your drug.

Time and Costs to IND and Clinical PoC

The earlier you can achieve IND and clinical PoC, the earlier you can prove the potential of the platform and the more likely you can attract further venture or pharma funding or possibly even exit. To estimate timelines to IND you could analyze the regulatory dossiers of products that have been admitted to the market, the more recent the better, to understand what data is needed. Also look what types of data have been generated by competitors working in your target indications. Certain drug modalities would call for particular toxicology models or are more expensive to produce. For example, oligonucleotide therapeutics generally need to be developed in expensive cyno monkey studies and are also more expensive to produce than small molecules for instance. Once you have gathered information on all the steps that you need to take to IND you can estimate timelines and costs to IND. Timelines to clinical PoC can be estimated by following the steps described above. Clinical costs are determined by the number of patients you would be targeting for the clinical trial and also the types of analysis you intend to do on tissue and blood. There are also substantial geographic differences in the costs of clinical trials - the US is probably the most expensive country.

3. Commercial attractiveness

At this stage, you should have a list of diseases that your platform is uniquely qualified to tackle and that have strong scientific and clinical feasibility. Now it’s time to determine which of those ideas have the right commercial value and can attract high value partnerships with pharma. The key here is to identify diseases where your platform-derived therapeutic has the potential to either address an unmet need or significantly improve upon the standard of care either by improving efficacy, safety, convenience or costs (in that order of priority).

Unmet Need and Patient Population

Ideally you want to develop a drug that transforms the disease outcome for a large number of patients. Precision medicine is now common practice in oncology with many tumor indications being segmented in smaller biomarker-defined markets. These still represent considerable market opportunities that drive substantial partnering, licensing and M&A activity. In fact, oncology has consistently taken up been the dominant area of dealmaking in life sciences in the last years. There has been an increased interest in developing products for rare tumors, which account for 20% of all tumors and tend to have limited treatment options. But developing drugs for rare tumors has certain regulatory benefits, including 7 years of marketing exclusivity, and can have relatively low cost. Yet they also tend to have projected peak sales of around $250 million on average, so you should be aware that this might attract a different pool of pharma’s. You may think of the small patient populations in monogenic rare diseases that still represent substantial markets as they are offset by high treatment prices. However, in these types of diseases - where one dysfunctional mutation leads to a disease - treatments tend to have a much larger impact on the outcome of the disease which helps to justify these prices. For a complex heterogenous disease like cancer it is less likely that a treatment would cause such profound responses and is therefore unlikely to command these high prices. Organizations like the National Institute for Health and Care Excellence (NICE) calculate the cost-benefit ratio for all regulatory approved medicines and advice whether they should be re-imbursed, effectively controlling market entry. There are multiple examples whereby pharma had to lower prices as NICE was of the opinion that the benefits did not outweigh the costs. When calculating markets, it is best to take a conservative approach and base pricing on the current prevailing standard of care treatments and molecules with similar types of innovation.

Competitors

Your ability to replace a standard of care in a certain tumor type is influenced by the broader competitive landscape. It’s important to know the key competitors and assess the likelihood that they could beat your product on the way to the market. Competitors come from all kinds of angles and you should therefore have a radar in place with an wide range and be prepared for competitors flying by in stealth mode. It’s not only commercialized products, but any pipeline programs within larger pharma or smaller biotechs targeting the tumor you have in mind. And it’s important to know that from a regulator’s and patient’s perspective, how the drug works (MoA) is not so relevant. As long as the drug simply works better than the standard of care (efficacy) and has an acceptable safety profile, it can be admitted to the market. So should you benchmark against any competing agent in the target indication inclusive of other MoAs and other therapeutic options including different MoAs, drug modalities or treatment forms. For example, in certain blood cancers the treatment arsenal consists of chemotherapy, small molecules, antibodies, stem cell transplantation and CARTs. You need to be superior to all of these treatments if they are being or likely to be used for the treatment line you are targeting. It’s also important to evaluate how treatments targeting earlier treatment lines could impact the later treatment lines you are targeting. For instance, recent clinical trials testing neo-adjuvant treatment of melanoma with checkpoint inhibitors have showed profound and durable responses in the majority of patients. Some KOLs have even suggested melanoma might be curable in most cases. If confirmed, this not only limits the addressable market size, but also means you are dealing with a very different patient population by the time the subsequent standard of care treatment options have been exhausted.

Payer Value

Another aspect to factor in is how desperately a new therapeutic option is needed by patients. The last thing you want is to do is develop a novel, and likely expensive, drug for a disease that is a relatively minor inconvenience to patients or that can be controlled or mitigated by alternative means. Even if it ends up showing differentiated improvement, can patients (and payors) afford it and would they be willing to pay a premium? A good thing to do is to map the baseline efficacy, safety, convenience of use (e.g. route of administration, frequency of dosing) and costs of the current standard of cares. Then talk to medical KOLs to understand what level of improvement your product would need to bring on top of these things to convince them switching over to your product. In general, products that come with improved efficacy are better positioned to justify premium prices. But there are examples of blockbuster products like Abraxane (nab-paclitaxel: re-formulated paclitaxel) and Xeloda (Capecitabine: oral 5-FU) that merely improve on safety and convenience of use.

Partnership Interest

Whereas new markets and customers can be created in some industries (examples are TomTom, Uber and Apple’s paid music streaming model), this not so common in life sciences. Competition is the norm in our industry. If there are no competing biotechs and pharma in your space, the commercial opportunity is either limited or the technical challenge too high. You want to look for the amount of partnering, licensing and M&A that is going on in the tumor indication you are aiming for and furthermore what kind of deal terms are typical. In doing so, also verify whether deals take place on the pre-clinical or clinical PoC you defined above. If not, you will need to factor in extra cash and timelines to get to the deal inflection point. Other than actual indications, also evaluate the interest for the technology platform/drug modality you want to develop. Some maybe be out of fashion or come with substantial skepticism. Chemotherapy for example is not on the shopping lists of most pharma’s besides continuing to be a cornerstone treatment in oncology. The first oncolytic virus treatment, T-VEC, was approved for melanoma some time ago. However, this has not been a commercial success and neither have other oncolytic virus been able to impress in the clinic. It is important to note that strong external industry interest in a particular area can bring huge tailwinds to your program. In oncology, big pharma tends to copy shopping lists from each other. When a hype emerges around particular area’s or technologies, this can lead to a surge in competing deal-hungry pharma’s that may be less picky on the quality of the opportunity being served to them.

4. Strategic Alignment

So what should the focus within your company be? After meticulously narrowing down your list to the diseases that pass the platform edge, scientific/clinical feasibility, and commercial attractiveness filters, you have gotten to a shortlist of best PTFs. Each of these bring their own sets of pro’s and con’s and there may not be ones that stand out, so you may feel inclined to work on all of them. But there are only a few programs a company can work on and so you need to assess opportunities with one last, critical filter: strategic alignment. One way to think of this: PTFs tells you what you can work on, but this will tell you what you should work on.

There are three options for the pool of PTF candidates: out-license, partner or internal development. You may have identified opportunities outside of oncology or identified an opportunity in a certain pediatric tumor. In these case, explore the feasibility to out-license the platform to third parties solely to develop products in that disease area. Out-licensing not only forces focus, it’s also a good way to capture value for otherwise latent assets. Get in contact with potential licensees if they would be interested to license your platform and what would trigger them to do so. Ideally, you should spend zero of your own resources on proving the feasibility of this PTF, but parties may need a bit of preclinical data to become convinced.

In other cases, a particular disease may be a compelling choice, but requires extensive external expertise, third-party IP or infrastructure in order to succeed. In those cases, you could seek for complimentary parties willing to co-create and share value. You may not want to focus on maximizing the deal terms, particularly if it’s your first one; partnerships can be incredibly valuable for startups because they enable you to learn and develop capabilities in a cost-effective manner. Partners may be able to provide access to particular translational models, PD assays, disease-specific expertise that would otherwise take years to build. Or they could provide access to complex, expensive infrastructure, like cell therapy manufacturing, that you wouldn’t be able to build yourself. Partners may also hold critical IP on certain methods or certain building blocks of the medicines that you will be jointly developing. Finally, partnerships not only heighten the odds of securing your next financing round or partnering deal but also enhance the ability to negotiate favorable deal terms.

But hopefully there are PTFs remaining on your shortlist that are in the goldilocks zone, where you are uniquely positioned to independently develop a product to a major value inflection point and where you are confident that all the necessary resources can be built in-house. Ideally, you should develop at least two PTFs that require similar types of resources, so you can adapt to disappointing data or emerging competitors with strong products. Others can be held in reserve for when you are ready to expand the scope of your platform and company. Keep in mind all of the downstream implications of choosing a tumor type and drug modality as a core focus; it impacts who you hire and how you build certain functions, like your R&D competencies or the clinical experts you bring on board. For instance, you don’t want to be developing one PTF that is using a cell therapy approach and another one that is using a small molecule approach. Conversely, you don’t want to hire a clinical expert specialized in late-stage clinical development of an unrelated drug modality in a very different tumor.

You should spend a good degree of time to get this right as pivoting to a different direction when you are well underway is very costly. Investors won’t be happy that their money has been wasted and timelines to the exit are delayed. Some may not be that patient and willing to just write another cheque. Frankly, finding a good PTF requires a combination of rigorous analytical thinking, where I hope this canvas can provide some structure, and also gut feeling. I am sure you and your team will enjoy the intellectual challenge!

Acknowledgement: this article was based on an excellent blog from Andreessen Horowitz and adapted for oncology (https://a16z.com/2021/01/08/platform-disease-fit/)