AI & Medicine has a platform that has been applied successfully in the context of collaboration with multiple pharma, biotech, and academia. More at
Quantum Chemistry Service - MedAI. Quantum chemistry is the application of the basic principles and methods of quantum mechanics to study chemical problems.
The research scope includes the structure and performance of stable and unstable molecules and the relationship between structure and performance; the interaction between molecules; the collision and interaction between molecules and other issues. Method Molecular orbital method The molecular orbital method is the generalization of the atomic orbital to the molecule, that is, in the physical model, it is assumed that each electron in the molecule moves in the average potential field generated by all nuclei and electrons, that is, each electron can be determined by a single-electron function (electronic Coordinate function) to express its state of motion, and call this single-electron function the molecular orbital, and the motion state of the entire molecule is composed of the molecular orbitals of all the electrons in the molecule (linear combination of products). Complex Network Analysis Service - MedAI.
Complex networks generally exist in the real world.
The network cluster structure with small-world and scale-free statistical characteristics is one of the important topological properties of complex networks. The use of clustering algorithms in complex biological networks to reveal the cluster structure of biological networks is of great significance for analyzing the topology of biological networks and predicting their functions.
The study of complex network clustering methods has important theoretical significance and broad application prospects for analyzing the topological structure of complex networks, understanding the functions of complex networks, and predicting the behavior of complex networks. Drug Discovery - MedAI. Computer-aided drug design plays a vital role in drug discovery and development, and has become an indispensable tool in the pharmaceutical industry.
As molecular databases of compounds and target structures are becoming larger and more and more computational screening approaches are available, there is an increased need in compute power and more complex workflows. Thus artificial intelligence gains a great attention in pharmaceutical application scenarios. Whether analyzing small molecules, peptides, proteins, oligonucleotides or antibodies, MedAI provides full service and strategic support for companies seeking to apply In Silico Drug Discovery methods. We have access to industry standard hardware and software to apply computational chemistry, molecular simulations, and chemical informatics methods to your projects. Our team will work with you to design experiments and get the results you need to make critical decisions and advance your projects.
Drug-Drug Relationship Analysis Strategies Development - MedAI. Through network pharmacology analysis, two or more drugs are compared in terms of symptoms, side effects, gene expression, etc., so as to determine the similarities and differences between different drugs better and reduce the high investment in actual testing.
Moreover, based on the analysis results of network pharmacology, it can provide new ideas for " Drug Repositioning". Strategies Development Similarity analysis of ADMET properties The properties of ADMET refer to the absorption, distribution, metabolism, excretion and toxicity of molecules in the organism. The description of ADMET can help to eliminate compounds with bad properties of ADMET in time, in order to avoid costly structural modification later. Neoantigen Prediction - MedAI. MedAI, as an important division of MedAI, is a company that combines AI and biophysics for drug research and development.
Our expert team focuses on the development of macromolecular drugs in the field of tumor immunotherapy. The team has carried out research in the computational immunology laboratory and has a background in physical chemistry, machine learning, and immunology. What is Neoantigen? Neoantigens are newly formed antigens that have not been previously recognized by the immune system. Neoantigens can arise from altered tumor proteins formed as a result of tumor mutations or from viral proteins.
Prediction of protein-protein interaction - MedAI. Proteins rarely play a role alone.
They are often combined into "molecular machines" and have complex physical and chemical dynamic connections to undertake biological functions at the cell and system level. The key step to reveal the complex molecular relationships in living systems is to map the physical "interactions" between proteins. The complete map of protein interactions that can occur in organisms is called an interaction group. Protein-protein interaction (PPI) is a highly specific physical contact established between two or more protein molecules, which is the result of biochemical events generated by interactions, including electrostatic forces, hydrogen bonding, and hydrophobicity effect. Many are physical contacts that are associated with molecules between chains occurring in cells or living organisms in a specific biomolecular environment.
Molecular Dynamics Simulation Service - MedAI. MedAI has extensive experience in the field of molecular dynamics simulation (MD) services.
Over the years, our computational chemist have provided many simulation services to hundreds of pharmaceutical and biotechnology companies. MD simulation is a set of molecular simulation methods, which is a powerful tool for studying the interaction of biological macromolecules and chemical compounds, and condensed matter systems.
Through molecular dynamics simulation, researchers can obtain the motion trajectory of the atoms in the system and observe various microscopic details of the atomic motion process. Through the dynamic simulation of the research system, we can understand the movement and biological functions of biological macromolecules, the interaction mechanism between protein and small molecules, and the self-assembly process of nanomaterial molecules at the molecular level. Coarse-grained dynamics simulations - MedAI. Coarse-grained dynamics simulations Coarse-grained molecular dynamics simulation is a simulation method between all-atom simulation and mesoscopic simulation.
Compared with all-atom simulation, it can simulate large-scale dynamic behavior; compared with mesoscopic simulation, it can reflect more microscopic levels. Chemistry Services - MedAI. MedAI provides the biopharmaceutical industry with high-quality medicine and organic synthesis expertise, as well as a collection of unique, novel, patentable, and drug-like organic compounds for drug discovery.
Our team is composed of professional chemists who are experts in high-quality organic synthesis, medicinal chemistry services, screening libraries, and new organic molecules production with potential biological activity. Our reliable experience in the development of screening libraries has provided new chemical starting points for multiple client discovery programs. In Vitro Pharmacology - MedAI. In vitro pharmacology means studies on the biological effects of drugs and pharmaceuticals, conducted outside of living organisms.
Any new drug or pharmaceutical that enters the market is a product of a long and rigorous development, testing, and approval process. At the early stage of drug discovery, the most promising molecules ("leads") undergo further screening to generates high-quality data in a precise and timely manner. All these parameters including chemical's safety, toxicity, pharmacokinetics, and metabolism must be assessed in the pre-clinical trials phase. In vitro pharmacology can be used to: Safety & Efficiency Evaluation - MedAI. Safety aspects have become an outstanding issue in the process of drug discovery and development.
The International Conference on Harmonization (ICH) has founded a Safety Pharmacology Working Group. Exposure of a drug to the body by pharmacokinetic studies on absorption, distribution, metabolism and excretion has to be investigated at an early stage of development and can contribute to the selection of a compound for development. Toxicology experienced major achievements by the introduction of new methods, e.g., in silico methods, toxicogenomics and toxicoproteomics. Drug-target Relationship Analysis - MedAI. Drug targets refer to biological macromolecules that have pharmacodynamic functions in the body and can be acted upon by drugs, such as certain proteins and nucleic acids. They have targeted structures and target molecules related to specific diseases. The analysis of drug targets can reflect which structures of drugs can interact with the target molecules and produce curative effects, so as to achieve the purpose of curing diseases.
COVID-19 Drug repurposing - MedAI. The new coronavirus disease (COVID-19) has become a pandemic threat to public health. This is a respiratory disease that causes fever, fatigue, dry cough, muscle aches, shortness of breath and pneumonia in some cases. In severe cases, it can cause the respiratory syndrome of ARDSA, a kind of severe lung inflammation, so that a large amount of fluid accumulates around and inside the lungs, which may cause septic shock due to a sharp drop in blood pressure, and body organs will also Failure due to lack of oxygen. The incubation period of this coronavirus is approximately 1 to 14 days, at the same time, Symptoms and severity vary from patient to patient.
Elderly people, children under 6 years old, and patients with a history of asthma, diabetes, or heart disease are more susceptible to the effects of this disease which makes the immune system compromised. Multiple Targeting Design - MedAI. Target-based drug discovery has successfully produced targeted drugs. However, it is less effective for diseases with complex pathogenic mechanisms (such as cancer, inflammation, diabetes, and central nervous system diseases). By modulating multiple targets to achieve the desired physiological response, multivariate pharmacology is emerging as a new paradigm for the treatment of complex diseases. Drug molecules that can simultaneously modulate multiple targets are a simple method for network control.
As the risk of drug-drug interactions decreases, the reduction of pharmacokinetics and drug interactions requires safety profile testing. Multi-target drugs can also circumvent drug resistance caused by single target mutations or expression changes, because it is rare that multiple targets in different pathways or cascade pathways have simultaneous mutations.
Figure 1. Fragment-Based Drug Design - MedAI. The molecular structure of a drug, and each fragment that composes it plays its own role, so researchers envision combining or extending different structural fragments in order to obtain new drug molecules. This is theoretically feasible. According to this idea, Jencks et al. built the theoretical framework of FBDD in 1981, and as a result, the FBDD method began to be applied in the field of drug design. Different from screening millions of compound databases to directly search for drug-size molecules (drug-size, that is, molecules of the same size as the drug molecule), the FBDD method starts from screening small fragment structures, which are usually Contains less than 20 heavy atoms. The more complex the molecule becomes (the molecular structure becomes larger and the features become more), the more interactions with the protein are possible, and the interaction can be any protein contact, such as hydrogen bond interactions and hydrophobic interactions.
Structure-Based Drug Design - MedAI. Structure-based drug design is the design and optimization of a chemical structure with the goal of identifying a compound suitable for clinical testing-a drug candidate. Drug design service - MedAI. Experimental Validation Platform - MedAI. Fusion Analysis - MedAI. Introduction of Fusion Analysis Gene fusion refers to the fusion of some or all of the sequences of two different genes due to some mechanism (such as genome mutation) to form a new gene.
Gene fusion includes fusion at the genome level and fusion at the transcriptome level. At the DNA level, a new gene composed of two or more genes is called a fusion gene. At the RNA level, a transcript composed of multiple transcripts is called a fusion transcript. Antibody De Novo Design - MedAI. Genetic engineering drugs, antibody engineering drugs, blood products drugs, and vaccines are common biological drugs.
De novo design of antibodies binding specific epitopes could greatly accelerate discovery of therapeutics as compared to conventional immunization or synthetic library selection strategies. Computational approaches have the potential to dramatically reduce the resources required for antibody discovery while increasing success rates for challenging targets. Immunogenicity Assessment - MedAI. New technique, in combination with the use of artificial intelligence, allows fragments of antibodies to be screened for susceptibility to aggregation caused by structure disruption much earlier in the drug discovery process.
Protein/Antibody therapies can be highly effective in treating disease. The failure rate of protein candidates upon manufacturing at industrial scale is a significant problem, emerging in the late stage of development process. With the protein/antibody sequence information gathered into our database and getting bigger, the screening system is underdeveloped using AI methods. MedAI's AI platform has a range of proteins to screen and to determine which are more likely to progress through the development process. Affinity Maturation - MedAI. Antibody therapeutics are designed against a target protein, and are increasingly being used in cancer therapy. High affinity and selectivity are critical issues for antibody therapeutic capacity.
It is critical to be able to understand how certain amino acid substitutions will change the binding energy (affinity maturation). Docking algorithms have expanded into the protein–protein domain with current standards including ZDOCK, ClusPro, Haddock, RosettaDock and several others. Common to these methods are sampling techniques such as Monte Carlo or fast-Fourier transform, which aim to generate structural conformations that can be scored with a function which estimates the energetic favorability of two docked structures.
Rational engineering methods can be applied with reasonable success to optimize physicochemical characteristics of antibody drugs. CADD Platform - MedAI. AIDD Platform - MedAI. Protein/Antibody Development - MedAI. Data Analysis at AI & Medicine: PrediXcan Based Analysis and BSLMM Prediction. How Can Artificial Intelligence Facilitate New Drug Research and Development? Power of AI Only 21 Days from Target Discovery to Candidate Molecule! Analysis of Surgery Video - Protheragen - AI & Medicine. Surgery is about precision and efficiency. Artificial intelligence(AI) can be effectively trained to deliver a reliable and efficient segmentation and labeling of operative video into its constituent steps.
Medical Imaging - AI & Medicine. Intelligent Image Diagnosis - Protheragen - AI & Medicine. Artificial intelligence can support radiologists and pathologists as they use medical imaging to diagnose a wide variety of conditions. AI may also be able to help train radiologists on both normal and abnormal presentations of various organs and body systems so as to more easily identify related disease states and conditions. Our Missions - AI & Medicine. AI & Medicine Announces Pharmacokinetic/Pharmacodynamic (PK/PD) Modeling for Drug Discovery — AI & Medicine. On October 24, 2020, AI & Medicine, one of the forerunners in the AI-assisted medicine area, announces it now provides PK/PD modeling service to help scientists and researchers more efficiently screen drugs and thus accelerating the process of new drug development.
The company is known as an expert in applying artificial intelligence into drug discovery, personalized healthcare and various other medical applications. PK/PD modeling is a mathematical technique used to predict the effect and efficacy of drug dosing over time. “More specifically, pharmacokinetic models describe how the body reacts to a drug in terms of absorption, distribution, metabolism, and excretion. Pharmacodynamic models describe how a drug affects the body by linking the drug concentration to an efficacy (or safety) metric.
A Few Reminders for Applying Artificial Intelligence in Medicine — AI & Medicine. PrediXcan Based Analysis – Protheragen - AI & Medicine. Data Analysis - AI & Medicine. Molecular Docking – Protheragen - AI & Medicine. AI & Medicine Launches AI-Powered Drug Discovery Platform for the Science Community — AI & Medicine. De novo Drug Design – Protheragen - AI & Medicine. Structure Activity Relationship Analysis and Development – Protheragen - AI & Medicine. Biomarker Discovery – Protheragen - AI & Medicine. PK/PD Modeling - AI & Medicine. AI-assisted Retrosynthetic Analysis – Protheragen - AI & Medicine. Lead Drug Screening, Scoring, and Ranking – Protheragen - AI & Medicine. Structure Activity Relationship Analysis and Development – Protheragen - AI & Medicine. Benefits Brought to Pharmaceutical Industry by Artificial Intelligence - AI & Medicine.
What is Artificial Intelligence - AI & Medicine. Biomarker Discovery – Protheragen - AI & Medicine. Machine Writing - Protheragen - AI & Medicine. Machine Translation - Protheragen - AI & Medicine. Pharmacovigilance - Protheragen - AI & Medicine. Patient Screening and Recruitment - Protheragen - AI & Medicine. Prediction of Drug Crystal Form - Protheragen - AI & Medicine. Develop Drug Targets - Protheragen - AI & Medicine. Drug Research and Development Solutions - AI & Medicine. AI & Medicine.