Interest in generative AI has skyrocketed in 2023. While the generative AI market is already substantial, worth $10 billion in 2022 according to Grand View Research, it is set to balloon by a compound annual growth rate (CAGR) of 35.6% from 2023 to 2030. It’s no wonder that a slew of companies — including Exscientia, Insilico Medicine, Atomwise and BenevolentAI — are eager to tap the technology to expedite drug discovery.
Enter Synthetica Bio
The latest entrant in the generative AI scene is Laguna Beach, California-based Synthetica Bio. The startup aims to explore generative AI and large language models (LLMs) to enable real-time data processing. The company, founded by Simon Arkell and Alex Dickinson, entrepreneurs with a successful track record in companies like the predictive analytics firm Predixion, digital pathology startup Deep Lens, biotech Helixis and the molecular diagnostics firm Chromacode, has formed strategic partnerships to propel its platform development.
Strategic partnerships are at the heart of Synthetica Bio’s approach
Simon Arkell
Out of the gate, the company has a partnership with Microsoft that provides it with access to their cloud service, Azure, and a shared history of successful collaboration in the healthcare and life sciences sector. “We’re very early stage yet but we’ve committed to Microsoft and Azure within their program,” said Simon Arkell, CEO of Synthetica Bio.
Additionally, Synthetica Bio has formed a partnership with one of the largest healthcare data providers in the industry, allowing them to use de-identified data on more than 200 million American patients to fine-tune their models.
Synthetica Bio also differentiates itself from competitors with its trove of data from more than 220 million Americans. “But the secret sauce is that this is in a secure cloud,” Arkell adds, emphasizing the importance of data privacy and security in their operations.
User-centricity also key
Created to serve multiple departments within a pharmaceutical company, including marketing, drug discovery, and clinical trials, the platform’s user-centric design empowers analysts, scientists and other users to pose data-driven questions directly, sans a dedicated data science team. “We’re building an environment where the analyst, the PhD, the clin ops staffer, the scientist can query the data without going through a data science team,” Arkell elaborated.
In addition to its multi-disciplinary utility, Synthetica Bio prioritizes user-friendliness. “We’re operating at the abstraction level above the data, where a drag-and-drop UI helps user personas construct their own copilots,” Arkell noted.
The promise of generative AI in an ever-evolving landscape
Arkell stressed the importance of keeping pace in a swiftly progressing field. “The beauty of a modular, orchestration platform leveraging many large language models and data…means the platform will stay cutting-edge, continuously gaining intelligence and never becoming obsolete.”
Flexibility is also an attribute of Synthetica Bio’s platform. “Users can run it either on our secure cloud, where they can apply their data for training and tuning, or host the software on their own cloud instance,” Arkell explained further, spotlighting the security and adaptability of their offering.
Arkell believes embracing generative AI is vital for companies to stay relevant. “Many companies have initiatives underway and budgets,” he said. “The very largest firms we’ve engaged already have data science teams and need to adopt generative AI to remain competitive.”
Synthetica Bio is targeting an underserved market
When asked about conversations so far with biopharma companies, Arkell noted significant interest in the industry for generative AI, with many firms actively experimenting and building out teams. He noted that fully capitalizing on the technology requires major investments that may be out of reach for smaller players.
Arkell explained that Synthetica Bio is devoting itself full-time to building an enterprise-level AI platform. He believes mid-sized biopharmas without large data science teams represent a prime target market, as they lack the internal resources to harness generative AI themselves but recognize the need for tailored AI technologies.
Looking ahead, Arkell sees Synthetica Bio’s platform as a tool for those mid-size companies without extensive data science capabilities. “We’re encountering high demand from organizations with extensive data, needing quick insights from their resources,” he noted.
Filed Under: Data science, machine learning and AI
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