The State of TechBio

ANALYSIS
By Luca Parisi, Daniel Chancellor, and Lucie Ellis-Taitt

These are exciting times for the TechBio community, from the pioneering start-ups and academics to their industry partners and investors. Generative artificial intelligence (AI) has now become part of everyday conversation through the success of ChatGPT and other programs, raising awareness of some of the tools that underpin the technology aspect of TechBio companies.

Meanwhile, biotech drug pipelines are as deep as ever with the validation of new modalities and patient data being generated at pace. For those companies operating at this interface, the use cases are maturing rapidly with real-world examples. The evolution of the TechBio community will impact the broader life sciences industry in a critical way. It will need to be integrated into the whole continuum of R&D.

This includes AI-driven drug discovery, whereby algorithms are enabling the design and optimization of novel small molecules and proteins with accuracy and scale that conventional drug discovery cannot match. Furthermore, existing treatments can be repurposed using AI-derived biological insights, with multi-factorial matching of patients to clinical trials that are designed to maximize the likelihood of success. Such processes will expedite the overall R&D process and drug development pipeline, lowering the degree of attrition during late-stage clinical trials, thus addressing key industry productivity challenges.

Furthermore, expansion and integration of patient data into early R&D decision making will be transformational for the future of healthcare. The broad adoption of multiomics tools is generating new insights into fundamental human biology and precision medicine. Diseases are increasingly viewed as a function of such biomarkers, which ultimately guide diagnosis, treatment, and connected care in the real-world setting.

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The cost and complexity of drug development requires experienced and committed partners. Therefore, the long-term success of TechBio is dependent upon the flow of investment and alliances with mature life sciences companies. This collaborative model, long established between big pharma and emerging biotechs, has proven many times over an ideal framework to develop new treatment options for patients. The broader state of TechBio can therefore be gauged through such deal-making activity.

It is difficult to capture the totality and nuance of TechBio ― which sits at the intersection of many different disciplines ― within any standard industry dataset. Citeline tracks global dealmaking activity in life sciences and assigns an AI classification to companies and deals where relevant, which can be used as a proxy for the TechBio universe. Exhibit 1 summarizes total financing and partnership activities involving AI.

Exhibit 1: Growth in TechBio Financing and Partnering Activities

Source: Biomedtracker, July 2023

It is an understatement to say that TechBio deal-making is on the rise. Life sciences companies raised a record £9.4bn investment in 2022 to further advance their AI platforms and assets, with this total having doubled every year since 2018. The number of alliances with biopharma partners is also following a similar trajectory, although their value is more volatile and heavily swayed by milestone components. Nevertheless, £263m in upfront payments was a record for 2022, spread across 81 separate partnerships.

The first half of 2023 has not been able to sustain the incredible amount of global activity within 2022. Speaking to In Vivo, Ivan Griffith of BenevolentAI Limited explained: “Investment and growth have slowed down and people are waiting to see critical readouts and data that validate the thesis that AI can significantly benefit drug discovery and reduce attrition.”

Deal values and volumes are down sharply as TechBio has not been immune to broader market uncertainties, although the UK has been an outlier. Here, TechBio companies are on track to exceed last year’s £161m in fundraising across 10 deals, with seven financings bringing in a total of £87m so far in 2023. This resilience is enabling the UK TechBio ecosystem to secure a prominent position in the global rankings. Across both financings and alliances, the UK is second only to the US for TechBio deal-making over the last 18 months (see Exhibit 2).

Exhibit 2: Financing And Partnering Activity By Geography

Source: Biomedtracker, July 2023

UK Companies Driving the AI Revolution

The UK TechBio ecosystem contains a range of different technologies and business models. Companies such as Exscientia plc and BenevolentAI are at the vanguard, becoming fully fledged biotechs with a blend of strategic alliances, such as multi-year strategic partnerships between BenevolentAI and AstraZeneca, out-licensed assets, and internal drug pipelines. Several others are bidding to make the transition from discovery science to clinical-stage candidate. Earlier in the lifecycle, there are a range of venture capital-backed service providers with specific capabilities in a particular R&D step, therapy area or diagnostic tool.

Having raised close to $500m from investors during its 2021 initial public offering and private placement, Exscientia has now progressed six assets into clinical trials, either through strategic alliances or as internal R&D programs. Three of these are under development by Sumitomo Pharma for CNS disorders, while the remaining programs target cancer and inflammatory diseases. Of note, the ELUCIDATE basket trial of a CDK7 inhibitor is underway, with broad potential application in a range of prevalent solid tumors. Exscientia also regained control of assets discovered in collaboration with Bristol Myers Squibb against the complex cancer targets LSD1 and MALT1.

Prior to founding Exscientia, CEO Andrew Hopkins spent 14 years at Pfizer Inc. and in academia, pioneering projects using data mining and machine learning in the pharmaceutical industry. He expects the biggest gains for AI in biopharma to come from precision medicine.

He told In Vivo: “The area, I believe, where we will see the greatest impact is truly making personalized medicine a reality.” In 2022, the company published results from the EXALT-1 trial. EXALT-1 was the first prospective interventional study of its kind. “Predictions made by the platform proposed which therapy would be most effective for late stage hematological cancer patients based on testing drug responses ex vivo in their own tissue samples,” Hopkins explained. “When we looked at results, about 25% of the patients four years later were progression free.”

London-based CHARM Therapeutics is one of the few TechBios to secure financing so far in 2023. New investment from Nvidia raises total fundraising to date to $70m and adds to an already impressive syndicate of venture capital firms. This investment will further fuel the development of Charm’s DragonFold platform that can identify novel molecules through protein-ligand co-folding. In addition, Charm secured its first industry partner in Bristol Myers Squibb, leveraging DragonFold to discover novel molecules against targets of interest. BMS is able to exercise options to license and develop any compounds that arise from this collaboration. “Protein structure prediction using deep learning has the opportunity to greatly impact biopharma, not just due to having the 3D structure of any protein, but also the related algorithms people will develop inspired by it (e.g., folding a PROTAC, E3 ligase and POI all at the same time),” Laksh Aithani, CEO of CHARM Therapeutics, told In Vivo at the start of 2023.

Also bucking the broader biotech downturn in 2023, BIOS Health received new funding from a range of investors, including the TechBio fund Selvedge Venture. BIOS is a trailblazer in combining AI technologies and precision neurology, and is providing its capabilities to the US National Institutes of Health as part of the REVEAL study. The ambition is to sequence neural biomarkers to elucidate the link to various disease states, much as genetic sequencing has resulted in significant breakthroughs for drug discovery in cancer and rare diseases.