Sightera Biosciences generates proprietary drug‑response datasets from therapy‑resistant, end‑stage patient‑derived tissues and applies AI‑driven discovery to design novel small‑molecule therapeutics for high‑unmet‑need diseases. Their platform combines ex vivo high‑throughput screening of clinically annotated samples with deep‑learning algorithms to identify both monotherapy and synergistic drug candidates tailored to patient biology. This patient‑centric approach aims to produce first‑in‑class compounds that address treatment‑refractory cancers.
Funding
€3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AQFounders
Product
Problem
Drug discovery often relies on preclinical models that do not accurately reflect the biology of therapy‑resistant or end‑stage patients, resulting in low translation rates and limited options for diseases with high unmet medical needs.
Solution
Sightera Biosciences addresses this gap by generating proprietary, clinically annotated datasets from patient‑derived, heavily pre‑treated tumor and tissue samples using advanced ex vivo platforms and high‑throughput robotic screening. These datasets capture monotherapy and synergy responses, providing a human‑centric view of how therapies interact with patient biology. The company then applies deep‑learning AI algorithms trained on this data to design novel small‑molecule candidates, including molecular glue degraders and ADC payloads, that are optimized for activity in refractory patients and for combination with standard of care. Biomarker‑driven stratification is integrated into the design process to match the right patients with the right molecules, aiming to increase clinical success rates. The end‑to‑end pipeline spans discovery, hit‑to‑lead, candidate selection, and IND‑enabling stages, delivering AI‑designed therapeutics for oncology, fibrosis, and other high‑need indications.
Target Audience
Primary customers are pharmaceutical and biotechnology companies, as well as research organizations, seeking AI‑enhanced discovery of therapeutics for oncology, fibrotic diseases, and other indications with high unmet medical needs.
Features
- Ex vivo patient‑derived tissue platforms that preserve the biology of heavily pre‑treated, treatment‑refractory tumors.
- High‑throughput robotic drug screening generating proprietary monotherapy and combination response datasets.
- Deep‑learning AI models trained on clinically annotated data to predict activity, synergy, and optimal biomarker signatures.
- Design of molecular glue degraders and small‑molecule ADC payloads tailored for refractory patient populations.
- Biomarker‑guided patient stratification integrated into molecule design to enhance clinical trial success.
- End‑to‑end drug development workflow covering discovery, hit‑to‑lead, candidate selection, and IND‑enabling stages.