Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

AION Labs, Powered by BioMed X, Launches Third Global Call for Application: Artificial Intelligence for Design and Optimization of Antibodies for Targeted Therapies

AION Labs, a first-of-its-kind innovation lab spearheading the adoption of AI technologies and computational science to solve therapeutic challenges, and German independent research institute BioMed X, announced the launch of the third global call for application to identify biomedical scientists and inventors to form a new startup at AION Labs’ headquarters in Rehovot, Israel.

The chosen AION Labs startup team will be sponsored by several industry-leading partners and supported by the Israel Innovation Authority (IIA) and Digital Israel office. The sponsors of this call for application are AstraZeneca, Israel Biotech Fund, Merck, Pfizer and Teva Pharmaceuticals, with close support from Amazon Web Services (AWS).

Recommended AI News: Brivo Delivers Enterprise Security Solutions to Global Customers Including Afterpay and Angi

Antibody treatments continue to be the standard of care for several disease areas and have emerged as cornerstone therapies during the current pandemic. However, despite being primary treatment modalities for over two decades, the cycle times for the discovery and optimization of therapeutic antibodies can still span several years. In order to achieve developable antibody therapeutics exhibiting target-specific binding, stability and scalability, several biophysical parameters need to be streamlined. The use of artificial intelligence (AI) has the potential to broaden the explored sequence space, accelerate the selection of fully optimized antibodies, and shorten overall lead discovery times by successfully predicting relevant parameters.

AION Labs is inviting computational biologists, bioinformatics and cheminformatics scientists, AI researchers, and antibody or protein engineers at academic and industry research labs worldwide to propose the development of a next-generation computational platform to optimize antibodies for targeted therapies with enhanced properties, including developability or manufacturability, stability, aggregation, immunogenicity, pharmacokinetics and tissue distribution. The ultimate solution is an AI platform that receives sequences of binders and generates novel variants with optimized IgG sequences, biophysical and targeting properties. The goal of the AI algorithm is to make an existing antibody a better drug while reducing design iterations, optimization of cycle times and lowering attrition rates. The AION Labs pharma partners involved in this project will provide a wealth of data for model training and their expertise in setting specifications and evaluating the outcome. Original ideas that go far beyond the current state-of-the-art are being encouraged.

Related Posts
1 of 38,619

Recommended AI News: IBM and SAP Strengthen Partnership to Help Clients Move Workloads from SAP Solutions to the Cloud

“AION Labs is eager to tackle yet another pharmaceutical R&D challenge,” said Dr. Yair Benita, CTO of AION Labs. “We’re anticipating another strong round of applications, and look forward to working together with the chosen startup to develop a cutting-edge solution to substantially improve the design and optimization of antibodies for targeted therapies.”

As part of the online application procedure, interested candidates are requested to submit a competitive project proposal. After a preliminary short-listing round, candidates will be invited to a five-day innovation boot camp in Rehovot. With the support of experienced mentors from the pharma, tech and VC industries, the winning team of scientists will be trained and guided during a fully-funded incubation period of up to four years towards becoming an independent startup.

Recommended AI News: Siemens Adds Intelligence-Based Design to Xcelerator Portfolio With Latest Release of NX

[To share your insights with us, please write to]

Comments are closed.