Triomics, a healthcare startup based in San Francisco, has successfully raised $15 million to enhance oncology workflows through generative artificial intelligence (GenAI).
This investment, led by renowned Silicon Valley investors, aims to automate tasks in cancer centres, reducing manual inefficiencies and improving patient care.
Manual data handling in oncology is a significant challenge, with vast amounts of unstructured data residing in free-text patient records. This often requires labor-intensive chart reviews, slowing down critical processes like clinical research and patient management.
Triomics, co-founded by Sarim Khan and Hrituraj Singh, tackles these issues through an innovative solution combining an oncology-focused large language model (OncoLLM) and tailor-made software. This facilitates automated data processing at scale, significantly cutting down processing times.
The primary users of Triomics’ technology are clinical research nurses, coordinators, and registrars involved in oncology research and care, primarily within academic medical centres and cancer institutions.
The technology assures faster patient-trial matching, expediting potentially life-saving clinical trial enrolments. Pharmaceutical companies benefit by accelerating their study enrolments, leading to quicker drug development and market entry.
Oncology staff face ongoing burdens in manual data processing.
Extracting insights from free-text health records, which constitute about 80% of medical data, is a painstakingly slow process often leading to provider burnout.
These delays affect patient-trial matching, stalling clinical innovations.
The potential of generative AI is harnessed by Triomics through OncoLLM, a model tailored for oncology-specific data.
This specialised AI understands cancer care terminology, improving accuracy in trial matching and data extraction from patient notes.
Explainability, the ability to elucidate AI-driven decisions, is key in oncology to ensure trust in the technology, which Triomics achieves through interpretable models.
Triomics distinguishes itself from general AI companies by focusing exclusively on oncology, offering software specifically designed for complex healthcare challenges.
Legacy technologies lack the scalability and cost-efficiency that Triomics provides, setting it apart in the market.
The company’s commitment to user-centric design and ongoing collaboration positions it for success in the AI healthcare domain.
The $15 million funding round was backed by leading investors such as Y Combinator, Lightspeed, General Catalyst, and Nexus Venture Partners.
With this capital injection, Triomics aims to further refine its AI solutions, sustaining a competitive edge in the burgeoning health tech arena.
Performance-based agreements with partners ensure that financial benefits are realised only after demonstrable returns are achieved.
By streamlining EHR-to-EDC integration, Triomics enhances data efficiency across healthcare systems, while enabling registrars to abstract data effectively for tumour registries.
These capabilities support a future-proof infrastructure for healthcare advancements.
Triomics’ funding marks a transformative shift towards automated oncology workflows, promising substantial improvements in efficiency and patient care.
With a strategic focus on AI innovation and industry collaboration, the company is well-positioned to lead advancements in healthcare technology.
