Using synthetic biology and AI to address global antimicrobial resistance threat
Driven by overuse and misuse of antibiotics, drug-resistant infections are on the rise, while development of new antibacterial tools has slowed.
3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs
Professor James Collins discusses how collaboration has been central to his research into combining computational predictions with new experimental platforms.
Sean Luk: Addressing the urgent need for better immunotherapy
The MIT senior helps design proteins that spur the immune system to fight cancer and other diseases.
A better DNA material for genetic medicine
With its circular single-stranded DNA molecules, MIT spinout Kano Therapeutics plans to make gene and cell therapies safer and more effective.
Prognostic tool could help clinicians identify high-risk cancer patients
Using a versatile problem-solving framework, researchers show how early relapse in lymphoma patients influences their chance for survival.
MIT chemists synthesize a fungal compound that holds promise for treating brain cancer
Preliminary studies find derivatives of the compound, known as verticillin A, can kill some types of glioma cells.
MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases
BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.
MIT study finds targets for a new tuberculosis vaccine
Using these antigens, researchers plan to develop vaccine candidates that they hope would stimulate a strong immune response against the world’s deadliest pathogen.
New method could improve manufacturing of gene-therapy drugs
Selective crystallization can greatly improve the purity, selectivity, and active yield of viral vector-based gene therapy drugs, MIT study finds.
Designing better, longer-lasting medicines
Adding amino acids to certain protein-based medications can improve stability and effectiveness. New MIT research demonstrates how it works.
AI maps how a new antibiotic targets gut bacteria
MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.
Biogen groundbreaking stirs optimism in Kendall Square
The gathering of Biogen and MIT employees, business leaders, and public officials celebrated the first building to be constructed at Kendall Common.
MIT researchers develop AI tool to improve flu vaccine strain selection
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
A new model predicts how molecules will dissolve in different solvents
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
Using generative AI, researchers design compounds that can kill drug-resistant bacteria
The team used two different AI approaches to design novel antibiotics, including one that showed promise against MRSA.