Experts have identified a handful of biotech research areas that remain strongly in the crosshairs of VC investment and will likely shape the industry in coming years.
The most successful funding areas are those that revolve around delivery platforms, in which a treatment’s delivery method, or vector, is in place and has been tested. These have the potential to deliver cures for diseases that have resisted treatments thus far.
One technological platform can be used to deliver multiple types of cures (Sherkow 2016). This means biopharma companies that have already done the early R&D to create specific drugs can collaborate with biotechs and use their technology platforms to deliver those drugs. This method of essentially outsourcing early R&D has become more common – and more lucrative – in recent years. Moderna’s mRNA therapeutics platform, for example, was in high demand for biopharma companies across multiple disease arenas even before the COVID-19 pandemic (Morrison 2016). From 2019 to 2021, two-thirds of the $52 billion invested globally by VC companies into therapeutic-based biotech firms went to startups with platform technologies (Leclerc et al. 2022).
Five examples at the financing forefront are cell therapy, next-generation gene therapy, precision medicine, machine learning–enabled drug discovery, and approaches for reaching “undruggable” disease targets (Leclerc et al. 2022). It is likely that companies with proven success in delivery platforms for these areas will be the most successful in attracting biotech VC funding.
- Cell therapy for cancer
Cell therapies that combat multiple forms of cancer garner a significant share of biotech VC funding. Since the advent of chimeric antigen receptor (CAR) T-cell therapy in 2017, which was revolutionary in treating hematologic malignancies, there is hope that similar progress might soon be made for treating other types of disease using a new cycle of cell therapy technologies dubbed “cell therapy 2.0.” This includes solid tumors, which comprise over 90% of adult cancers but have faced significant challenges for treatment (Leclerc et al. 2022).
Despite the small number of approved cell therapies, there has been a substantial uptick in funding every year over the past decade. This is a relatively new research space, but one with massive potential, and investors have shown consistent interest in companies with strong pipelines (Kemler and Lohr 2022).
- Next-generation gene therapies
Next-gen therapies that improve upon existing gene therapies (e.g. CRISPR-Cas9 gene editing) account for an increasingly large share of funding and spending in biotech and biopharmaceuticals. As with cell therapy, despite its relative novelty and risk, investors expect gene therapy to reap increasingly more approvals and returns in the years to come (Kemler and Lohr 2022).
It is estimated that as of June 2022 there were 400 gene therapies in development, and that by 2025, these therapies will potentially account for 20% of novel drugs coming to market (Leclerc et al. 2022). As scientists’ ability to locate, snip, or insert genetic material improves, the possible applications of next-gen therapies will likely see a massive boom. Experts hope this will offer treatments for rare diseases that have thus far been out of reach.
An example of next-gen gene therapy, one that came to the forefront during the COVID-19 pandemic, is the use of new RNA-editing tools to produce vaccines. Though it is commonly stated that COVID-19 vaccines were produced in “record time,” the basic research behind this new approach has been ongoing for decades. Now, with these new tools in place, we could be seeing a new "plug and play" vaccine model, where the success of the COVID-19 vaccines fuels future successes against other COVID-19 variants — and indeed other pathogens altogether (Gardner 2021).
- Precision medicine
Precision medicine, one of the most exciting areas for biotech VC funding, will allow individual patients to receive tailored treatment designed specifically for their genome, rather than broad, generalized treatments that can often cause harmful side effects. Personalized treatments will reflect a given patient’s drug intolerances, relevant biomarkers, and other molecular considerations (Leclerc et al. 2022). This kind of customization makes each treatment more valuable. Furthermore, successful personalized therapies streamline healthcare by omitting unnecessary costs, which is a big draw for investors (Pappas Capital 2012).
Precision medicine will also impact advances in early detection of various diseases, as well as minimize the need for invasive surgeries or other procedures. The ability to create and deliver a customized treatment with minimal side effects is a complex endeavor, but the implications are profound (Leclerc et al. 2022).
Although precision medicine is still in its early stages, several breakthroughs have been made. Many biotechs are using cutting-edge technologies to address the gaps, and VC investors have consistently put funding toward these areas since 2017 (Leclerc et al. 2022). Investors are especially drawn to therapies and platforms that can demonstrate substantially better outcomes through real clinical data (Pappas Capital 2012).
This is a space where platform technologies are essential. Though spending a large number of resources to develop a therapy geared toward a small number of people would be cost-prohibitive, platforms that can deliver a variety of bespoke treatments to a larger number of patients are particularly attractive to investors. Some recent examples include companies that have developed virtual delivery platforms for in-home care, mechanisms for speeding up clinical trials, and programmable technologies that can use data to build precision therapies (Bio-IT World 2022).
- Machine learning for drug discovery
With an increasingly massive knowledge base of drugs, their interactions, and the complex genetic makeup of diseases, machine learning is a potentially invaluable tool for sorting through known variables and excluding therapies that are not likely to succeed. Machine learning tools for drug discovery are still in their infancy, but as they become more robust, the ability to computationally select the right candidates to create a drug cocktail or staged approach will streamline the process for researchers to discover and develop new therapies (Leclerc et al. 2022).
In the same way that other areas of science have advanced on the efforts of those that came before, the use of novel machine learning approaches will allow researchers to build on existing drug discovery efforts and optimize their use of precious resources, both time and money alike (Leclerc et al. 2022). Machine learning has its potential place at every stage of the pipeline, from compound screening to the development of individualized drugs (Kirkpatrick 2022).
Researchers and investors hope that with the right application, machine learning could speed up drug development, reduce costs, uncover hidden possibilities from massive repositories of data, and, critically, increase success rates in the clinic. This is another space where partnerships between pharmaceuticals and platform biotechs are essential (Kirkpatrick 2022). And it seems investors are focusing not just on the what, but the who — rather than being spread among startups with glamorous technology, more money has been funneled toward an increasingly small number of established companies with obvious AI expertise on staff (Kahn 2021).
- Reaching new drug targets
Finding compounds that can reach new drug targets is another area with tremendous commercial potential. In a 2020 report, Genentech estimated that of 4,000 known targets, only a quarter had a drug that could actually reach them (Genentech 2020). These targets often have complications that make them unsuitable for conventional drugs such as small molecules or monoclonal antibodies — for example, they are prone to drug resistance, or the effects of successfully binding an existing drug are slight (Leclerc et al. 2022). The companies that solve these problems will become essential.
There are a range of novel approaches under investigation to break through to these validated but “undruggable” disease targets. This includes identifying new binding sites, finding ways to degrade proteins instead of binding small molecules, or finding new disease targets altogether (Leclerc et al. 2022). As of June 2022, for example, there were some 20 targeted protein degraders, or TPDs, in clinical trials. The proof of principle for this approach has led to a significant upswing in investor interest, as well as the number of partnerships between pharmaceuticals and TPD platform companies (Nasir et al. 2022).
Future Outlooks for Startups
As biotech startups work to bring their new technologies into the picture, they would be wise to take certain considerations into account.
Interest rates, for example, have a heavy influence on a startup's success in securing VC funding. When federal banks increase interest rates, this can have an adverse effect on VC funding. And unlike other startups, biotechs must do their initial work to prove their viability with little room for cost-cutting — for example, reducing salaries or staff (Fleming, 2022). In a fiercely competitive arena, this means biotech companies are uniquely incentivized to make their work look attractive to investors.
However, as difficult as economic conditions might be for biotech startups, society has begun to see the impact that biotech successes have on the public’s health and wellbeing. Because of this, biotech VC funding may be down from 2021, but those with solid potential to impact human health have good reason to expect a bright future — one with plenty of VC funding to support their goals.