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ArticleWhy AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
ArticleAACR 2026 part 1: AI design, precision biology and the next wave of oncology innovation
At AACR 2026, industry leaders discussed how oncology R&D is moving beyond isolated technological advances towards integrated discovery systems.
ArticleAI builds dual-action cancer drug targeting PKMYT1
Research published in Nature Communications shows how generative AI can be used to design complex dual-action cancer drug candidates. Insilico Medicine has developed a PKMYT1 degrader that both eliminates the target protein and blocks its activity, demonstrating the growing role of AI in advanced drug discovery.
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Why AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
AACR 2026 part 1: AI design, precision biology and the next wave of oncology innovation
At AACR 2026, industry leaders discussed how oncology R&D is moving beyond isolated technological advances towards integrated discovery systems.
AI builds dual-action cancer drug targeting PKMYT1
Research published in Nature Communications shows how generative AI can be used to design complex dual-action cancer drug candidates. Insilico Medicine has developed a PKMYT1 degrader that both eliminates the target protein and blocks its activity, demonstrating the growing role of AI in advanced drug discovery.
More Oncology
Why AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
AACR 2026 part 1: AI design, precision biology and the next wave of oncology innovation
At AACR 2026, industry leaders discussed how oncology R&D is moving beyond isolated technological advances towards integrated discovery systems.
AI builds dual-action cancer drug targeting PKMYT1
Research published in Nature Communications shows how generative AI can be used to design complex dual-action cancer drug candidates. Insilico Medicine has developed a PKMYT1 degrader that both eliminates the target protein and blocks its activity, demonstrating the growing role of AI in advanced drug discovery.
Improving selectivity in antibody–drug conjugates
Promatix Biosciences is developing a new generation of bispecific antibody–drug conjugates using proprietary membrane proteomics data to identify highly selective target pairings. CEO Dr Michael Hunter explains how the company’s TXPro database enables discovery of previously unexplored tumour biology to improve therapeutic index and reduce on-target/off-tumour toxicities in solid tumours.
Platinum-antibody conjugates enhance immunotherapy while reducing chemotherapy toxicity
A novel platinum(IV)-antibody conjugate platform delivers low-dose chemotherapy directly to tumours, upregulating MHC-I expression and enhancing anti-PD-1 responses while minimising systemic exposure. The approach addresses immune evasion mechanisms that limit checkpoint inhibitor efficacy.
Metabolic vulnerabilities identified in rare Fibrolamellar liver cancer
Researchers have identified metabolic vulnerabilities in Fibrolamellar cancer, a rare liver malignancy affecting adolescents and young adults, using functional profiling and mass spectrometry. The findings suggest chemotherapy-resistant tumours may be susceptible to metabolism-targeted therapies.
AI platform identifies novel gp130 inhibitor for colorectal cancer
An AI-assisted drug discovery platform using transfer learning has identified a promising gp130 inhibitor for colorectal cancer.
Cholesterol trafficking disruption targets TP53-mutant cancers
Scientists have identified a mechanism to starve aggressive cancers by blocking cholesterol transport within tumour cells, offering a targeted approach for malignancies carrying TP53 mutations, present in half of all cancers.
New study indentifies Golgi apparatus proteins as cancer growth drivers
Researchers at the Harrington Discovery Institute have identified cellular mechanisms involving Golgi apparatus proteins that drive cancer progression by trafficking growth factor receptors to cell surfaces.
RAGE receptor identified as key driver of age-related metastasis
Georgetown Lombardi researchers have identified RAGE, an inflammatory receptor, as a key mediator of age-related breast cancer metastasis.
CAR T cell therapy eliminates glioblastoma tumours in preclinical study
A next-generation CAR T cell immunotherapy targeting the urokinase receptor has eliminated treatment-resistant glioblastoma tumours in preclinical models.
YAP1 protein found to drive chemotherapy resistance in small cell lung cancer after treatment
University of Texas MD Anderson Cancer Center researchers have discovered that YAP1 protein expression emerges after chemotherapy treatment in small cell lung cancer, enabling resistant cancer cells to survive and proliferate.
Protein modifications control drug binding and efficacy in new study
New research reveals that subtle chemical changes to proteins after synthesis play a critical role in determining drug-protein interactions.
Bispecific antibody targets Wnt co-receptors for diabetic macular oedema treatment
Preclinical data presented at ARVO 2026 demonstrate therapeutic potential of targeting Gpr124 and Lrp6 Wnt co-receptors to restore blood-retina barrier integrity in diabetic macular oedema and wet age-related macular degeneration, with trispecific candidate NVQ501 advancing towards IND-enabling studies.
Organoids and Organ Chips: Improving Decision-Making in Early Drug Discovery
Early drug discovery has no shortage of models, but predicting what will translate to patients remains difficult. This report examines how organoids, organ-on-chip systems and imaging technologies are used to measure drug response, analyse resistance mechanisms and assess how well findings reflect clinical outcomes in human-relevant models.
New SEE-CITE technology maps drug-protein interactions with targeted precision
A UCLA-led research team has developed SEE-CITE, an advanced photo-crosslinking technology that enables direct comparison of drug-protein binding interactions, potentially aiding the discovery of safer, more effective therapeutics across multiple disease areas.