French startup Iktos has secured €15.5 million in Series A funding for its AI-powered drug discovery platform. The round was co-led by M Ventures and Debiopharm Innovation Fund, with participation from Omnes Capital, and will enable Iktos to develop its technology further and expand its SaaS software offering. The company is set to launch Robotics, an end-to-end drug discovery platform that uses AI and automation of chemical synthesis to accelerate drug discovery timelines. Additionally, the company will expand its application of solutions to biological products, allowing it to offer fully integrated drug discovery services to the pharmaceutical industry. Iktos, which was founded in 2016, uses a technology platform for deep learning-based drug design that offers significant productivity gains in upstream pharmaceutical R&D.

Artificial Intelligence (AI) in drug discovery is now on a steep rise. A growing number of companies compete to develop new drugs faster, cheaper, and with a much higher success rate by using AI tools at all crucial stages of the drug discovery pipeline. Most of the players in this quickly expanding market are oriented towards big pharma, which is routinely investing billions into drug development. Such a partnership is tempting not only for startup companies but also for established leaders in the field of AI-based drug development because it provides stable multi-year contracts backed up by the financial resources and infrastructure of the pharmaceutical giants. As a result, end-to-end AI-based drug discovery services are tailored for large corporate customers.

Insilico Medicine and Fosun Pharma have announced an important strategic collaboration agreement. The partnership was announced yesterday at the 40th Annual J.P. Morgan Healthcare Conference. The companies will use Insilico's AI driven drug discovery platform to advance the discovery and development of drugs targeting a number of different diseases. The collaboration includes an upfront payment of $13 million plus an equity investment in Insilico Medicine of an undisclosed amount. The collaboration will combine Insilico's end-to-end AI-driven drug discovery platforms and Fosun Pharma's clinical development and commercial expertise to discover and develop a portfolio of novel therapeutics.

Polaris Quantum Biotech is reinventing drug discovery, reducing the time it takes to find candidate molecules for drug development from the typical three years to just four months. As with other successful efforts to redesign established processes, Polaris is betting on scalability and automation. The startup, co-founded by Shahar Keinan and Bill Shipman, came out of stealth a year ago, revealing the first-ever drug discovery platform using a quantum computer, cost-efficiently scanning billions of molecules from a large chemical space. Having worked in the drug development industry for years, Polaris' founders decided to try and address the two major challenges they identified: The technology used and the business model. "We wanted to solve both of these problems together," says Polaris' CEO, Shahar Keinan.

Auransa Inc., an artificial intelligence (AI) company developing precision medicines in areas of unmet medical needs, and Polaris Quantum Biotech (POLARISqb), a quantum drug design company, announced a research collaboration addressing therapeutics for neglected diseases disproportionately affecting women. The partnership seeks to discover treatments that may tackle many such diseases, and their complementary expertise promises to seek solutions that elude medical research. Auransa is an AI-driven biotech company, with a pipeline of novel compounds for various diseases. Auransa's proprietary predictive computational platform, SMarTR Engine, uses computational approaches to tackle disease heterogeneity to predict targets and compounds, generating insights from molecular data. POLARISqb built the first drug discovery platform using quantum computing, making the process ten times faster.

With Canadian infection rates recently breaking the 1 million mark and deaths topping 23,000 and counting, and the global infection rate reaching 132 million, with nearly 3 million deaths to date, intervention is critical. "By targeting human proteins necessary for the coronavirus lifecycle, we are developing therapeutic strategies applicable to future strains or variants" said Dr. Bo Wang of the Vector Institute. "Unlike high throughput screens, accurate AI predictions aimed at specific human-based, antiviral targets provided us with a risk-adjusted strategy to search for drug-repurposing opportunities using scientifically accurate experiments with high biological relevance." The discovery of capmatinib's antiviral activity is a shining example of the power of collaborative research programs. The Vector Institute team's graph convolutional network (GCN) identified possible human targets relevant to COVID-19, which fed directly into Cyclica's PolypharmDB - a database for finding repurposing opportunities, generated using Cyclica's deep learning approach MatchMaker.

With a slew of partnerships with large pharmaceutical companies under its belt and the successful spin out of at least one new company, Atomwise has already proved the value of its machine learning platform for discovering and commercializing potential small molecule therapies for a host of conditions. Now the company has raised $123 million in new funding to accelerate its business. "Scaling the technology and scaling the team and scaling what we've been doing with it," says chief executive officer Abe Heifets when asked about what comes next for the eight-year-old business. Atomwise has already signed contracts worth $5.5 billion with corporate partners that include Eli Lilly & Co., Bayer, Hansoh Pharmaceuticals and Bridge Biotherapeutics. Smaller, earlier-stage companies like StemoniX and SEngine Precision Medicine are also using Atomwise's tech.

Naheed Kurji is the President and CEO of Cyclica, a Toronto-based biotechnology company that leverages artificial intelligence and computational biophysics to reshape the drug discovery process. Cyclica leverages artificial intelligence and computational biophysics to reshape the drug discovery process. Can you discuss in what way AI is used in this process? Technology has played a critical role in drug discovery dating back to the '80s. However, the drug discovery and development process is still very inefficient, time consuming and expensive, costing more than 2 billion dollars over 12 years.

From developing drug treatments to predicting the next hotspot, artificial intelligence may help researchers, healthcare workers, and everyday people offset the impact of the coronavirus. As the worldwide fight against coronavirus COVID-19 continues, companies and governments around the world are pulling out all the stops in an effort to stave off the pandemic's worst impacts. One tool in that toolbox that might prove particularly useful is artificial intelligence (AI). Even though AI has been around since the 1960s, it's only been in the past few years that its adoption outside of science labs and research institutions has really taken off. Perhaps the most common application of AI people have come into contact with today are virtual assistants like Apple's Siri and Amazon's Alexa, which rely on natural language processing (NLP) algorithms to understand human speech.

Charles River Laboratories International, Inc. (NYSE: CRL) and Atomwise, Inc. today announced the formation of a strategic alliance that offers clients access to Atomwise's artificial intelligence (AI)-powered, structure-based, drug design technology, which allows scientists to predict how well a small molecule will bind to a target protein of interest. By removing sole reliance on empirical screening, AI enables drug researchers to test an extremely large and diverse chemical space in a matter of days and move through the optimization process quickly by focusing only on those compounds predicted to have improved target-binding attributes. This alliance combines two industry-leading drug discovery platforms: Atomwise's AI technology and Charles River's unique portfolio of end-to-end drug discovery and early-stage development capabilities and expertise. Leveraging Atomwise's AI technology and Charles River's integrated drug discovery platform has the potential to significantly streamline the hit discovery, hit-to-lead, and lead optimization process for clients' research efforts. Founded in 2012, the San Francisco Bay Area-based venture has raised over $50 million in venture capital financing.