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    "Digital Disruption
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    AI and Predictive Informatics Solutions

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About Us

EinNext Biosciences is a data-driven solution provider for the biopharmaceutical and biomedical industries. With the power of transformative technologies such as Big Data and AI, our aim is to digitally transform these industries.

R&D Services

Pharma & Biopharma

Biomedical Industries

In silico based protein engineering

  1. ML for enzyme/antibody engineering

    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 modeling.

  2. Quick and accurate solutions

    Since our approach uses only sequence information for modeling, our algorithms provide quick solutions without compromising on accuracy.

  3. Focus on novelty and patentability

    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.

  4. Additivity of mutants for property improvement on a large scale

    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.

  5. Cutting-edge enzyme/antibody engineering algorithm and new training data

    Our IT and ML experts relentlessly working on the integration of novel ML approaches into our existing methods and addition of new data from our own research will continue to strengthen our ML model prediction accuracy.


  1. Complete Image-to-Computation studies

    We perform segmentation of DICOM images obtained from standard imaging methods.

  2. Hemodynamic & FSI analysis in Intracranial aneurysms

    Computational fluid dynamics has proved beneficial in analyzing the hemodynamics in the aneurysm before and after treatment. We learn the interaction of stent with blood through strongly coupled fluid-structure interaction studies.

  3. Intracranial Aneurysm rupture prediction

    Since a while, computational fluid dynamics has proved its mettle in predicting the rupture status of intracranial aneurysm. We use the association between aneurysm rupture sites and hemodynamic features to conclude its rupture state.

  4. Rupture mechanism of cerebral aneurysm

    We research on the rupture mechanism of intracranial aneurysm. The study of mechanism of rupture is immensely valuable as it could save many lives.


  1. Myocardial Ischemia prediction through hemodynamics

    We predict myocardial stenosis through computational hemodynamics with the understanding of reserve volume of heart.

  2. Structural validation of stents - bending behavior, recoiling, dog-boning & fore-shortening

    Virtual testing of stents includes its structural analysis through computational methods and the results are matched with the FDA standards.

  3. Virtual Fatigue testing & Failure analysis of stents

    We analyze the long run effects of stents from its fatigue and durability testing. Strain-based and Stress-based life predictions are made using non-linear finite element studies taking into consideration the effects of cardiac pulsatile loading and stent-vessel oversizing.

  4. Stent migration and FSI studies

    The bio-mechanical interaction between a balloon-expandable stent and a stenotic artery gives a better understanding on the possible areas of artery injury during the stent deployment and areas of non-uniform contact pressure after the stent apposition, due to a non-uniform stent expansion.

  5. Design optimization & evaluation of vascular stents

    Better optimized stent designs could improve the efficacy of stents. Each design variant undergoes strict evaluation through finite element analysis.


  1. Study the airway resistance and airflow through the tracheobronchial tree

    The CT scan image obtained is rendered to generate the airflow model and computational fluid dynamics performed in the model gives the airflow resistance and velocity in every location. This gives us an understanding of the pathophysiology of lower airways that is useful in obstructive lung diseases.

  2. Identify the relationship between total cross sectional area and airflow velocity in tracheobronchial tree

    The air velocity is tend to vary according to the total cross sectional area of flow. We take into consideration the relation to identify the areas of constricted airflow in the airway tract. The associated recirculation and vorticity is also be evaluated using the approach.

  3. Analyze the pulmonary drug delivery mechanism

    Designing of an effective inhaler requires the knowledge to drug particle deposition in the airway tract on using the inhaler. With the help of CFD analysis we identify the locations of excess deposition and the locations devoid of drug that could help in optimizing the design of asthma inhalers.


  1. Design of orthopedic implants

    To obtain clinically acceptable design is very important as it serves in terms of both patient safety and optimal performance of implants. We model the implants keeping this in mind ensuring accuracy and safety.

  2. Screening of orthopedic implant & prosthesis designs

    We explore performance of various orthopedic implants and their significance based on design changes through finite element analysis.

  3. Knee & Hip Implant performance evaluation

    We work to ensure proper range of motion and synchronic performance of implants. The most important movements of joint are measured to meet the ideal levels.

  4. Durability assessment of Prostheses & Orthoses

    Having knowledge of the implant durability is very essential. With this thought we develop methods for testing prostheses with repetitive load cycles to assess their performance and life. We also work on simulating different ranges of motions with different load cycles.

  5. Human gait analysis

    The most popular and a systemic process is human gait or walking cycle. We track the movements of joints on each step of gait cycle to ensure that the implant is properly patent to the joint. Study of different types of gait and its interaction with joint and implant is quantified i.e., percentage of abnormal deviation from a normal gait.


  1. Material characterization of dental fillers

    Different filling materials have varied interactions with the dental tissues. We use finite element approach to identify the change in stiffness due to various fillers and the resulting stress concentrations that may cause an undesirable break of the loaded tooth.

  2. Study the cement flow pattern in a system

    Through computational fluid dynamics we analyze the cement flow pattern, optimum amount of cement required and the speed of crown seating while joining crown and implants using cement. This reduces the cement overflow and its related side effects for the patient.

  3. Implant abutment design & cement application analysis

    We re-design implant to retain the excess cement within the implant abutment and study various implant designs using CFD to understand the cement overflow.

  4. Assessment of patient-specific dental implants for better fit

    We carry out the 3D analysis to evaluate the biomechanical behavior of patient-specific dental implants and its appropriate redesigning under different loading conditions. It helps to improve preparation designs, indicates the right material or combination of materials to be used in various load and stress conditions in order to reduce material and/or tooth failure in clinical practice.

Executive Board

Albert Einstein. G, President and Chief Executive

Is the President and CEO of EinNext Biosciences. He is also the Founder and Head of Operations of EinNel Technologies. He has had a distinguished professional experience in Computer Aided Engineering in the field of automotive and bio-medical engineering. He is passionate in developing innovative technology in medical science and leading technology focused companies.

Mr. Einstein has obtained his Bachelor of Engineering from Bharathiyar University, Coimbatore and Master of Engineering in Computer Aided Design from Anna University, Chennai, India.

Nelson Joseph. G, Technical Director

Is the Technical Director for Software Development in EinNext Biosciences and also the co-founder of EinNel Technologies. He has rich professional experience in software development in the field of automotive and bio-medical engineering. He has specialized experience in designing data structure, API development, Scientific Data Visualization, Automations and FOSS. He is focused in developing innovative software products in Medical Engineering.

Mr. Nelson has received his Master of Computer Application from Anna University, Chennai, India.

Chandrasekar, Chief Financial Officer

has over 25 years of Finance and Internal Auditing experience and is presently serving as Chief Financial Officer at EinNext Biosciences. He takes the main responsibility for finance control, planning & analysis, investors relations and enterprise analytics. He also has established CA Associates and works for auditing services.

Mr. Chandrasekar has received his Master of Commerce from Madurai Kamaraj University, Tamil Nadu, India and also he is an experienced Cost and Works Professional (CWA).

Technical Board

Nataraj Balakrishnan, Research Head

Nataraj holds his M.Tech. in Bioinformatics from SASTRA Deemed University, Thanjavur, India. He has fifteen years of experience working for a Pharma R&D. He has expertise in the computational assisted directed evolution of enzymes; antibody engineering and also in small molecule drug design using the structure and ligand-based approaches. He is also an AI/ML enthusiast to apply the approaches for antibodies and small molecules drug discovery. He is currently pursuing his PhD at Anna University, India, in the topic of antibody-drug design for treating breast cancer using AI/ML approaches.

Roselyn J Newton, Research Assistant

Earned her Masters in Technology specialized in Biotechnology from VIT University, Vellore. Her research work carried out in the University of Bordeaux, France was based on mixed mode chromatography. Her other areas of research includes establishing diagnostic tests for Fanconi Anaemia, an inherited bone marrow failure syndrome.

Akash Ravikumar, Technical Executive - Medical IoT & AI

Akash Ravikumar manages the Medical IoT and AI team. He has wide experience in embedded systems, edge computing, machine learning and deep learning. He leads the execution team in Medical IoT & AI related projects.Akash holds his Master’s in Electronics Engineering from Kaunas University of Technology, Kaunas, Lithuania.

Merlin S, R&D Engineer - Software Development

Merlin directs and leads all software development operations at EinNel Technologies. She holds her Bachelor's in Electronics and Communication Engineering from Anna University and Master’s in Software Systems specialized in Data Analytics from BITS, Pilani, India.

Case Study

Specific Problems

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.

Specific Problems

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.

Specific Problems

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.

EinNext Transformative Technologies

AI and Predictive Informatics Solutions


For more info and support, contact us!

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+91 (44) 2278 2028