ML for Enzyme/Antibody Engineering
ML algorithms to solve enzyme/antibody engineering problem...
Cutting-edge enzyme/antibody engineering
ML experts relentlessly working on the integration of novel ML approaches...
EinNext employs Artificial Intelligence to revolutionize Antibody drug discovery and Enzyme engineering. With high tech efficiency in machine learning models followed by the meticulous molecular dynamics simulation-based validation approaches, EinNext’s computational protocol strikes the industry standard in the modern era of AI assisted computation-aided antibody/enzyme Engineering.
The company’s hybrid-based approach, which uses AI modelling of Antibody/Enzyme mutational modelling followed by thorough investigation of the predicted model using in-silico molecular dynamics simulation and free energy estimation strategy gains more confidence to come up with the precise target approach which greatly reduces time and cost when compared to directed evolutionary approaches. EinNext is bound to formulate strong partnerships, and collaborates along the academia and pharmaceutical industry to disentangle multiple interdisciplinary problems. The company was established in 2015 which is mapped in Chennai, India.
We strongly believe that the future of healthcare is antibody-based drug and the antibody design will be automated by Artificial Intelligence that helps to accelerate drug discovery pipeline and aids in developing many precise and tailor-made medicine to cure diseases for which the drugs are yet to be found.
We develop ML algorithms to solve enzyme/antibody engineering problem using amino acid sequence information and the fitness of mutants using wet-lab experimental data. ML approaches outscore the accuracy of prediction of other forms of computational modelling.
Since our approach uses only sequence information for modelling, our algorithms provide quick solutions without compromising on accuracy.
The robustness of our algorithms helps analyse all theoretical combinatorial possibilities of a mutant sequence. This enables us to explore functional mutants in untested regions of the enzyme/antibody ensuring novelty of mutants.
A unique feature of our ML algorithm is that it provides a reliable solution for the additivity of single mutants (epistasis). An accurate prediction of epistatic of mutants in our approach, that would otherwise impair prediction in other approaches, leads to property improvement of the enzyme/antibody on a large scale.
Our IT and ML experts are relentlessly working on the integration of novel ML approaches into our existing methods and addition of new data from our own research which will continue to strengthen the accuracy of our ML model prediction.
Atherosclerosis or arteriosclerotic vascular disease (ASVD), in which plaque builds up inside arteries,the most common cause for mortality in the developed world.Endovascular procedures like angioplasty for atherosclerosis treatment provide an alternative to open-surgery and require minimal invasion into the human body Angioplasty is used extensively for the treatment of peripheral vascular disease to restore correct blood flow and for the treatment of coronary heart disease and involves stent insertion.However, in-stent restenosis, a repeated narrowing of artery post stent implantation, limits the clinical success of angioplasty, which is caused by mechanical factors, such as wall strain distribution and blood flow induced wall shear stress and local arterial wall stress. Considering the huge expense for the experimental evaluation of stent deployment, we used an alternative route of computational numerical methods to understand the mechanical behavior of stent implantation.
According to a recent survey conducted among 400 adult volunteers who underwent clinical and radiological evaluations, Dr.Nakagawa reported the incidence of un-ruptured Intracranial Aneurysms (IA’s) to be as high as 7%. Brain aneurysms are often discovered when they rupture, causing bleeding into the brain or the space closely surrounding the brain called the subarachnoid space causing a Subarachnoid Hemorrhage (SAH). SAH can lead to hemorrhagic stroke, brain damage and death. Hence, it is required to determine whether the particular aneurysm has a high risk of rupture so that it can be treated before bleeding occurs. There are certain cases where neurosurgeons fail to judge the risk of rupture even with their profound experience and decide not to meddle with it. Such was a problem that was shared with us by a group of doctors wherein we are supposed to predict the rupture status of IA’s.
In the current fast growing busy life, dental ailments have become a certainty in every common man’s life. Almost 5 out of 10 people have dental issues and end up in dental implants in some or the other stage of their life. The most undesirable part of this is the trauma and swelling suffered by the patients post dental implantation. Repetitive treatments on such affected areas are never welcoming by patients. Even expert dentists may not succeed in providing happy smiles even after proper fixation of such artificial tooth. We took up this challenge and initiated an effort in this regard to evaluate dental implant designs for efficient and pain-free fixation.
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