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August 1, 2023Retinal Implants
August 1, 2023BenevolentAI
The Benevolent Platform allows scientists to decipher the vast and complex language that underpins human biology and find new ways to treat diseases.
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Based on solid technology foundations and cutting-edge technology, the Benevolent Platform allows scientists to decipher the vast and complex language underpinning human biology and find new ways to treat disease. Their data fabric facilitates strong synergies through the entire drug research and development chain, and their information graph is therapeutic field agnostic. This information is fed into their patented knowledge graph, which collects and contextualizes pertinent data from many machine-curated interactions between disorders, genomes, and drugs.
AI Aspects
Benevolent create technology in the service of science to enhance human knowledge and encourage the creation of new therapies for the thousands of diseases for which there is no cure.
They use artificial intelligence (AI), deep learning, and other cutting-edge technology to reimagine how medicines are found and created. Their goal is to re-engineer drug development and bring life-changing drugs to patients in desperate need.
New and more effective drugs are being developed
Many of the more used medications are ineffective for patients. BenevolentAI uses AI and machine learning models and techniques to help determine what receptors and pathways are causing disease and what targets they need to modulate to cure the disease, allowing us to engineer experimental drugs that function better for patients.
Increasing the pace at which life-changing drugs are delivered
A drug will take a decade or longer to develop, and the vast majority of experimental drug programs struggle. They will speed up new drug development and maximize efficacy by re-engineering drug research and identifying why patients are more likely to react to therapy.
New therapies for rare and untreated diseases are being sought
The cost of bringing a new drug to market is billions of dollars, leaving multiple epidemic fields ignored by the existing economic paradigm. They will reduce drug manufacturing costs and give patients new hope by using advanced technologies.(1)
Benevolent Platform
Raised on powerful data foundations, this platform helps scientists interpret the extensive and complex code in human biology and encourages them to find new options to treat disease. Benevolent data fabric allows powerful synergies around the entire drug discovery and development methods.
Improving knowledge and reasoning
Their system pipeline pulls information from different organized and unstructured biomedical information sources and clergy members and normalizes it through data fabric. Their information chart covers this, extricating and contextualizing the significant data, and comprises countless machine-curated connections between illnesses, genes, and drugs.
Novel target identification
Connection surmising AI models assist with foreseeing potential sickness focuses that might be disregarded by researchers. Their gene expression-based models assist them with recognizing proteins that are differentially communicated in healthy and sick cells. This information-driven TargetID strategy improves hypothesis volume and results in excellent objective decisions.
Patient-specific treatments
Ordinarily, illnesses have been characterized by manifestations or areas in the body, not by their fundamental patient-explicit molecular components or pathways. Benevolent platform-applied AI models empower researchers to decide the correct system to modulate and distinguish patient endotypes most likely to react to treatment.
Generating drug-like molecules in fewer cycles
The synthetic space for investigation is extensive, and a small part of it can be applied to making drugs. BenevolentAI expanded models enable chemists to assess a vast number of molecular constructions, create drug-like particles, and configure better medications in fewer cycles.
BenevolentAI drug programmes
BenevolentAI has built up a developing pipeline of medication programs reaching out from early revelation to the facility. The company center on illness territories with highly neglected clinical needs like neurology, immunology, and oncology, and the desire and capacity to investigate beyond.(2)
BenevolentAI financial aspects
BenevolentAI, one of the leading British AI companies, has been estimated at more than $2 billion since its latest funding round, in which the company secured $115 mm in financing. The funds will be utilized to diversify the company’s offering into vastly different industries, like energy storage, manufacturing, and agricultural areas, by bolstering its current use in pharmaceuticals. In addition, BenevolentAI has been selected as one of the most promising companies in the AI industry by Fierce Medtech. More promising news, BenevolentAI, and AstraZeneca joined a strategic collaboration to discover new drugs for chronic kidney disease and idiopathic pulmonary fibrosis..(3)
ML Provides Insights into Neurodegenerative Disease Mechanisms and Has the Potential for Fast Diagnosis and Treatment
Machine Learning Proposed for Protein Binding Sites
Deep learning machines have been suggested for pocket matching. DeeplyTough encodes the 3D structure of protein binding sites, and when data is analyzed through machine learning, it accurately matches the pocket binding sites. Specifically, this network can provide a three-dimensional graphic of protein pockets into descriptors vectors by measuring and introducing the Euclidean distances that could be compared efficiently.
Three benchmark datasets were performed, which revealed remarkable results regarding data provided from TOUGH-M, a dataset comprising 505,116 positive and 556,810 negative protein pocket pairs. The negative pocket pairs study with small distances false positives suggests false-positive results are possible due to an integrated network of pocket pairs measured through distances generated by DeeplyTough.(5)
COVID-19: Combining Antiviral and Anti-Inflammatory Treatments
COVID-19 and severe acute respiratory syndrome (SARS) are characterized by an exaggerated inflammatory response, and for SARS, there is no correlation between viral load and worsening of symptoms.
The BenevolentAI system identified a target and a potential therapy against SARS coronavirus 2. The drug targets are the numb-associated kinase (NAK), the inhibition of which reduces the viral infection in vivo. Baricitinib, a drug approved for rheumatoid arthritis (RA), is a potent and selective Janus kinase (JAK)-STAT signaling inhibitor with a high affinity for NAK and has the advantage of a single dose a day and an acceptable side effect profile. This work demonstrates that this technology could assist the fast development of drugs.(6)
Mechanism of Baricitinib Support AI-Predicted Testing in COVID-19 Patients
Baricitinib is a JAK1/JAK2 inhibitor approved for the treatment of RA. The drug has the virtue of inhibiting NAK, AAK1, and GAK, which stimulate host viral propagation. The study found that baricitinib inhibited the pro-inflammatory cytokines in patients hospitalized with COVID-19. Using samples from a randomized trial in RA, researchers showed significant declines in interleukin 6 (IL-6) levels (a predictor of death in COVID-19 patients) using baricitinib as treatment. In a liver spheroid experiment, baricitinib reduced cellular infection by blocking viral propagation. In a case series study from Italy, patients with bilateral COVID-19 pneumonia, the drug was associated with clinical, radiologic, and viral improvement parameters, including a decrease in CPR and IL-6 levels. The results showed the potential use of AI as a potential bedside therapeutic and the possible testing of baricitinib in randomized controlled trials treating COVID-19 patients.(7)