Lifeboat Foundation

The market introduction of the MR-Linac technology improves the patient care via the real-time imaging of the targeted PTVs. Conventional Water Phantoms with ferromagnetic material become prohibited due to safety reasons. To overcome this situation, LAP introduced the MR-compatible Water Phantom THALES 3D MR SCANNER. Dr Thierry Gevaert, medical physicist and co-ordinator at the UZ Brussel institute, will share his experience with the THALES 3D MR SCANNER during the commissioning of the MRIdian Linac of Viewray. Furthermore, he will highlight which benefits played an important role for his clinical workflow.

During the webinar you will also learn more about the THALES technology for commissioning and quality-assurance processes of conventional Linacs.

ISM001-055 demonstrated highly promising results in multiple preclinical studies including in vitro biological studies, pharmacokinetic and safety studies. The compound significantly improved myofibroblast activation which contributes to the development of fibrosis. ISM001-055’s novel target is potentially relevant to a broad range of fibrotic indications.

“We are very pleased to see Insilico Medicine’s first antifibrotic drug candidate entering into the clinic,” said Feng Ren 0, PhD, CSO of Insilico Medicine. “We believe this is a significant milestone in the history of AI-powered drug discovery because to our knowledge the drug candidate is the first ever AI-discovered novel molecule based on an AI-discovered novel target. We have leveraged our end-to-end AI-powered drug discovery platform, including the usage of generative biology and generative chemistry, to discover novel biological targets and generate novel molecules with drug-like properties. ISM001-055 is the first such compound to enter the clinic, and we expect more to come in the near future [1].”

Previously, Insilico Medicine demonstrated its ability to generate drug-like hit molecules using AI with the publication of the Generative Tensorial Reinforcement Learning (GENTRL) system for a well-known target in record time [2]. It also demonstrated the target’s proof of concept by applying deep learning techniques for the identification of novel biological targets. This novel antifibrotic program combined these target discovery and generative chemistry capabilities. Notably, Insilico Medicine completed the entire discovery process from target discovery to preclinical candidate nomination within 18 months on a budget of $2.6 million.

Scientists in California tried to study Alzheimer’s disease from a different perspective and the results may have led them to the cause of the disease.

Researchers at the University of California-Riverside (UCR) recently published results from a study that looked at a protein called tau. By studying the different forms tau proteins take, researchers discovered the difference between people who developed dementia and those who didn’t.

The tau protein was critical for researchers because they wanted to understand what the protein could reveal about the mechanism behind plaques and tangles, two critical indicators doctors look for when diagnosing people with Alzheimer’s.

The race to find medical treatments for Covid-19—and future pandemics—is on, driving renewed investments by the healthcare and pharmaceutical industries in Real-World Data (RWD) and Real-World Evidence (RWE). A new report on AI and the real-world studies industry, from Deep Pharma Intelligence (DPI), Evomics Medical and The Yuan (an online forum focused on AI in healthcare, for which I am a contributor), provides fresh insights into this rapidly evolving patient-centric approach to increasing R&D efficiency, accelerating the introduction of new drugs, and improving health outcomes. Full Story:

Circa 2019

Researchers of Sechenov University and University of Pittsburgh described the most promising strategies in applying genetic engineering for studying and treating Parkinson’s disease. This method can help evaluate the role of various cellular processes in pathology progression, develop new drugs and therapies, and estimate their efficacy using animal disease models. The study was published in Free Radical Biology and Medicine.

Parkinson’s disease is a neurodegenerative disorder accompanied by a wide array of motor and cognitive impairments. It develops mostly among elderly people (after the age of 55–60). Parkinson’s symptoms usually begin gradually and get worse over time. As the disease progresses, people may have difficulty controlling their movements, walking and talking and, more importantly, taking care of themselves. Although there is no cure for Parkinson’s disease, medicines, surgical treatment, and other therapies can often relieve some symptoms.

Continue reading “Scientists listed ways of applying genetic engineering to treat Parkinson’s disease” »

Citizen journalist now close to death.

Citizen journalist Zhang Zhan is in a Chinese prison for reporting from Wuhan during the height of the city’s coronavirus outbreak in 2020. Her family says she is on hunger strike and could be near death. All calls for her release have gone unheeded.

Continue reading “China: Citizen journalist Zhang Zhan detained over Wuhan reporting | DW News” »

Researchers have developed a new approach to machine learning that ‘learns how to learn’ and out-performs current machine learning methods for drug design, which in turn could accelerate the search for new disease treatments.

The method, called transformational machine learning (TML), was developed by a team from the UK, Sweden, India and Netherlands. It learns from multiple problems and improves performance while it learns.

TML could accelerate the identification and production of new drugs by improving the machine learning systems which are used to identify them. The results are reported in the Proceedings of the National Academy of Sciences.

There’s also been a lot of interest in creating more versatile “living inks” made up of bacteria, which can be genetically engineered to do everything from deliver drugs to clean up pollutants. But so far, approaches have relied on mixing microbes with polymers that help provide the ink with some structural integrity.

Now, researchers have developed a new living ink that more closely lives up to the name by replacing the polymers with a protein made by genetically engineered E. coli bacteria. The researchers say this opens the door to seeding large-scale, living structures from nothing more than a simple cell culture.

The key to the breakthrough was to repurpose the proteins that E. coli cells secrete to stick together and form hard-to-shift biofilms. In a paper in Nature Communications, the researchers describe how they genetically engineered bacteria to produce two different versions of this protein known as a “knob” and a “hole,” which then lock together to form a robust cross-linked mesh.

The top 10 emerging technologies include self-fertilizing crops, on-demand drug manufacturing, breath-sensing diagnostics and 3D-printed houses. Check the full list of emerging tech.