Physicians and scientists join forces to develop the longevity medicine curriculum

 

Physicians and scientists highlight the importance of longevity medicine education and collaborate on the first longevity medicine course for physicians

16th of March, Tuesday, 2021 -- Longevity medicine is a rapidly evolving branch of preventative precision medicine that is specifically focused on promoting healthspan and lifespan, utilizing aging biomarkers commonly referred to as aging clocks. Over the past decade advances in AI and machine learning enabled the development of deep aging clocks (DACs) and other novel tools to track the rate of aging. In parallel novel preventative and therapeutic interventions have been discovered or progressed into clinical trials. Many medical and public health professionals do not have time to read the thousands of research papers covering this new field and actively engage in cutting-edge innovation in preventative medicine. And there are few educational resources that outline the benefits of longevity medicine. However, in order for the field to evolve, it is important that these materials are easily accessible for the broad medical community and presented at the level acceptable by the general medical practitioners.

In the comment titled "Longevity medicine: upskilling the physicians of tomorrow" (Lancet Healthy Longevity, 2021) Evelyne Bischof, MD, Morten Scheibye-Knudsen, MD, PhD, Richard Siow, PhD, Alexey Moskalev, PhD, summarise current findings on the main types of deep aging clocks, longevity medicine and reflect on the necessary education in this field.

Multiple institutions providing medical education are now actively seeking collaborations with artificial intelligence experts to create educational content that will help medical professionals acquire new skills in artificial intelligence for healthcare. However, it was not until 2020 when the first educational curriculum in longevity medicine for physicians was created by the team of scientists and clinicians, led by the artificial intelligence and longevity scientist and entrepreneur, Alex Zhavoronkov, PhD.

In connection with the article calling for more educational resources scientists launched the first longevity medicine course for physicians.

The course provided the physicians and other medical professionals with the introduction to the theoretical and practical basics of longevity medicine, which includes molecular mechanisms, theories of aging, biomarkers of aging, and geroprotector regimens. This course, as well as similar courses, provide medical and public health professionals with the baseline knowledge required to understand aging research, knowledge about longevity therapies available related to senescence-related processes, and the skills to examine biomarkers of aging and other age testing mechanisms. The course discusses advances in research in drug design, machine learning, omics, differential diagnosis, biogerontology, geroprotective interventions and healthcare organisations while also educating medical clinicians on how to implement them on a daily basis.

Physicians and medical professionals can register for this course at Udemy at no charge during the promotional periods, take the course at their own pace at any time, and receive a certificate of completion. The next promotion will transpire from 16th to 24th March 2021 on Udemy Platform (coupon codes: LONGEVITYMEDICINE, FREELONGEVITY2021) and students registering for this course will be able to start the course at any time and receive a certificate of completion.

The authors also agreed to collaborate on a course to be available free of charge to physicians and the general public at https://www.longevity.degree/

"Longevity physicians are looking for ways to reduce the gap between the current parameters, such as the current biological age, and the parameters of optimal maximum physical performance, such as the ideal biological age, predicted by deep learning. It is essential that practicing doctors have access to the appropriate longevity medicine education through a credible curriculum", said Evelyne Bischof, MD.

"The emergence of reliable markers for human aging now allows us to understand what interventions reduce the rate of aging. We are on the cusp of a new era in medicine where age-associated diseases and perhaps aging itself can be slowed or even halted. Education about interventions leading to healthy aging is paramount for allowing everyone a healthier and longer life", said Morten Scheibye-Knudsen, MD, PhD.

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The article is available as open access in Lancet Healthy Longevity:

Lancet Healthy Longev 2021 Published Online March 25, 2021

https://doi.org/10.1016/S2666-7568(21)00024-6

The first fully AI-designed Drug Candidate

 Both the biological target and the molecules were discovered using AI.

AI delivers a patentable small molecule preclinical candidate for a new target with demonstrated efficacy in both human patient cells and animal models for Idiopathic Pulmonary Fibrosis (IPF) in less than 18 months.

Dr. Feng Ren Appointed as Chief Scientific Officer of Insilico Medicine

 

Pharmaceutical veteran joins Insilico Medicine to apply Artificial Intelligence to build a portfolio of Insilico Medicine's proprietary assets and further pipeline development

HONG KONG, Feb. 22, 2021 /PRNewswire/ -- Insilico Medicine (the "Company"), a global leader in artificial intelligence for drug discovery and biomarker development, today announced the appointment of Dr. Feng Ren as Chief Science Officer ("CSO").

Dr. Feng Ren is a highly respected drug discovery and development leader with a demonstrated track record in both biology and medicinal chemistry.  He joins Insilico Medicine from Medicilon, a leading contract research organization ("CRO") providing drug discovery services to the biopharmaceutical companies globally. At Medicilon Dr. Ren served as a Senior Vice President, responsible for the drug R&D service business of the Chemistry Department and Biology Business Unit with a team of 600+ chemists and biologists.

Before joining Medicilon, Dr. Ren spent 11 years in the discovery and development of small molecule innovative drugs at GlaxoSmithKline ("GSK").  He served as the chief researcher, program leader, director and head of chemistry of Neurodegeneration DPU, a global drug R&D unit in neurosciences in GSK.

In his career, Dr. Ren successfully developed multiple clinical candidate compounds/clinical Phase I compounds for the treatment of non-small cell lung cancer, multiple sclerosis, psoriasis, inflammatory bowel disease, Parkinson's disease, and neuropathic pain.

Dr. Feng Ren, CSO of Insilico Medicine, added, "Insilico Medicine is a global leader in AI-powered drug discovery with demonstrated experimentally-proven capabilities in the discovery of novel biological targets and small molecule drug candidates. The data I have seen so far has been very impressive and it convinced me to join the company to build a comprehensive drug discovery team to employ the end-to-end AI engine to produce a portfolio of novel preclinical and clinical assets.  I believe the outstanding team at Insilico Medicine will lead the way in transforming the drug discovery and development paradigm using AI and significantly improve the probability of delivering new medicines to address current unmet clinical needs."

Dr. Ren holds a Ph.D. degree in Chemistry from Harvard University, a Master's Degree in Chemistry from the National University of Singapore and a Bachelor's Degree from the University of Science and Technology of China.

Dr. Alex Zhavoronkov, Founder and CEO of Insilico Medicine, said, "I am excited to have Dr. Ren to join Insilico Medicine.  Dr. Ren has a stellar track record in running several parallel drug discovery projects at the pre-clinical and clinical level and bringing effective drugs to market.  His capability in drug hunting enabled us to build a drug discovery team of top-notch biologists and chemists and will greatly accelerate our progress towards Insilico Medicine's vision of leveraging AI to progress our preclinical programs into clinic and start a large number of new programs to fulfill the growing need for novel medicines, effectively bring medicines to patients in need."

About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models: providing AI-powered drug discovery collaborations and software through its Pharma.AI platform (www.insilico.com/platform/) and developing its own pipeline of preclinical/clinical programs. The preclinical programs are the results of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents.

Website http://insilico.com/

Contact: polly.firs@insilicomedicine.com

Insilico announces MolGrow -- a new generative model for hierarchical molecular generation

Insilico presented its new molecular generation model at the 35th AAAI Conference on Artificial Intelligence 

February 11, 2021 - Insilico Medicine, a global leader in artificial intelligence (AI) for drug discovery and development, proposed a new molecular graph generative model called MolGrow at the 35th AAAI Conference on Artificial Intelligence on February 5, 2021.

The AAAI conference promotes research in AI and scientific exchange among AI researchers, practitioners, scientists, and engineers in affiliated disciplines. AAAI-21 has a diverse technical track, student abstracts, poster sessions, invited speakers. Insilico Medicine presented during one of the poster sessions.

The researchers introduced a novel model, based on the normalizing flows approach, which produces molecular structures from a single-node graph by recursively splitting every node into two. The hierarchical nature allows for precise modifications of the generated graphs using latent representations. The proposed model demonstrated improvement of distribution learning and molecular optimization metrics among graph-based models.

"We are happy to present our latest results on molecular graph modeling -- a novel approach that combines advantages of invertible models and hierarchical generation. We hope our research gives new insights and ideas on how to improve graph generators," said Max Kuznetsov, Research Scientist at Insilico Medicine.

"At Insilico Medicine, we have been developing generative models for chemistry since 2016. We developed and integrated many models into our generative chemistry platform -- Chemistry42. We continue improving our generative tools, and with this paper, we explored graph-based generators," said Daniil Polykovskiy, IT Director at Insilico Medicine. "Our new model, MolGrow, is the new state-of-the-art among node-level graph generative models on both distribution learning and molecular property optimization tasks."

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About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models; providing AI-powered drug discovery services and software through its Pharma.AI platform and developing its own pipeline of preclinical programs. The preclinical program is the result of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents.
Website http://insilico.com/

Insilico Medicine contact information

Polly Firs
polly.firs@insilico.com

Artificial Intelligence-based Biomarkers of Ageing

 

Syngenta Crop Protection and Insilico Medicine to Harness Artificial Intelligence to Transform Sustainable Product Innovation

 

• Multi-year collaboration will use artificial intelligence (AI) and deep learning to accelerate the invention of new, more sustainable products and technologies for growers
• Insilico Medicine is a world leader in using AI and deep learning for the faster and more efficient innovation of new active ingredients
• Syngenta will harness the immense potential and scope of AI to develop the next generation of sustainable crop protection solutions

BASEL, Switzerland, Syngenta Crop Protection is collaborating with artificial intelligence (AI) and deep learning company Insilico Medicine to accelerate the invention and development of new, more effective crop protection solutions that protect crops from diseases, weeds and pests, while also protecting ecosystems. By bringing new solutions to farmers faster and more efficiently through innovation, Syngenta will help them meet the ongoing challenges they face, in order to enhance productivity and meet global demand for affordable, quality food.

“This collaboration with Insilico Medicine means that Syngenta can harness the immense potential and scope of AI to develop the next generation of sustainable crop protection solutions as part of Syngenta’s $2bn commitment to innovation and sustainability,” said Camilla Corsi, Head Crop Protection Research at Syngenta. “This will further transform agriculture by providing farmers around the world with the tools they need to produce healthy, nutritious, affordable and sustainably grown food in the most efficient way, while also minimizing the environmental impact.”

Insilico Medicine has a proven track record and has delivered significant advances in pharmaceutical research, using AI and deep learning to design, synthesize and validate new ingredients. The same approach also has the potential to transform the development of new crop protection solutions that help keep plants safe, from planting to harvesting. Working closely with Syngenta, Insilico Medicine will use their AI-powered small molecule generative chemistry technology not only to invent molecules for active ingredients faster, but also actively design molecules that are more sustainable and environmentally friendly.

“We are very happy to collaborate with a company that is dedicated to developing safe and sustainable solutions for growers,” said Alex Zhavoronkov, PhD, founder, and CEO, Insilico Medicine. “Our artificial intelligence is designed from the ground up to produce very precise chemistry to protect human health, while ensuring short-term and long-term safety. This expertise is extremely valuable for crop sciences, and especially so for businesses whose top priority is the safety of their products. Syngenta is a progressive company with many brilliant scientists, and we will be working together to use artificial intelligence for the benefit of agriculture.”

“Our reputation as a global leader in innovation is built on a foundation of collaboration and our understanding of the challenges faced by growers,” Camilla Corsi also noted. “Working together with Insilico Medicine, combining our skills, knowledge and technologies, will help ensure that new and more effective crop protection solutions will be in the hands of farmers sooner.”

About Syngenta

Syngenta is one of the world’s leading agriculture companies, comprising of Syngenta Crop Protection and Syngenta Seeds. Our ambition is to help safely feed the world while taking care of the planet. We aim to improve the sustainability, quality and safety of agriculture with world class science and innovative crop solutions. Our technologies enable millions of farmers around the world to make better use of limited agricultural resources. Syngenta Crop Protection and Syngenta Seeds are part of Syngenta Group with 49,000 people in more than 100 countries and is working to transform how crops are grown. Through partnerships, collaboration and The Good Growth Plan we are committed to accelerating innovation for farmers and nature, striving for carbon neutral agriculture, helping people stay safe and healthy and partnering for impact.

To learn more visit www.syngenta.com and www.goodgrowthplan.com

Follow us on Twitter at www.twitter.com/Syngenta and www.twitter.com/SyngentaUS

About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models; providing AI-powered drug discovery services and software through its Pharma.AI platform (www.insilico.com/platform/) and developing its own pipeline of preclinical programs. The preclinical program is the result of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents. Website http://insilico.com/

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Cautionary Statement Regarding Forward-Looking Statements

This document may contain forward-looking statements, which can be identified by terminology such as ‘expect’, ‘would’, ‘will’, ‘potential’, ‘plans’, ‘prospects’, ‘estimated’, ‘aiming’, ‘on track’ and similar expressions. Such statements may be subject to risks and uncertainties that could cause the actual results to differ materially from these statements. For Syngenta, such risks and uncertainties include risks relating to legal proceedings, regulatory approvals, new product development, increasing competition, customer credit risk, general economic and market conditions, compliance and remediation, intellectual property rights, implementation of organizational changes, impairment of intangible assets, consumer perceptions of genetically modified crops and organisms or crop protection chemicals, climatic variations, fluctuations in exchange rates and/or commodity prices, single source supply arrangements, political uncertainty, natural disasters, and breaches of data security or other disruptions of information technology. Syngenta assumes no obligation to update forward-looking statements to reflect actual results, changed assumptions or other factors.

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Contacts

Syngenta

Media Relations
media.relations@syngenta.com

Head Crop Protection External Communications
Anna Bakola
+32 488 43 94 85
anna.bakola@syngenta.com

Insilico Medicine

Polly Firs
polly.firs@insilico.com