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Drug discovery software is used to develop new pharmaceutical drugs and test whether a newly created drug will be effective in treating a particular disease. Drug discovery software automates and leverages innovative technology that significantly cuts down on the arduous process of drug development, testing, and going to market.
Most drug discovery solutions offer screening, predictive analytics, modeling, simulation, and computational capabilities. Those functionalities help with tasks such as image analysis and clinical trial results submission, as well as ensuring accurate reproducibility. Researchers and scientists use drug discovery software to gain market intelligence, take advantage of advancements in drug design and synthesis, tackle evolving and adapting diseases, and maintain and manage the integrity of data as drugs transition from the discovery phase to the clinical trial phase.
To qualify for inclusion in the Drug Discovery category, a product must:
With its origins as a chemical drawing tool, ChemDraw has evolved steadily to become the leading chemically-intelligent solution for multiple disciplines from specialty chemistry to pharmaceutical drug discovery. Some chemists love to draw and some don't. But all of you have to share, report on, and publish your work in various formats, up to and including filing with the United States Patent and Trademarks Office. No matter which kind of chemist you are, or what your drawing and publishing req
Online, on-demand market research connecting you to the right healthcare stakeholders. MicroSurvey helps you design simple surveys, bringing you faster, quality data at a lower cost. Physicians complete short, 2-5 minute surveys they want to answer in the pauses of their day. Smart, on-demand technology designed to respect doctors’ time.
DSG’s eCaseLinkTM Drug Safety system streamlines the safety recording, reporting process, data entry on Serious Adverse Events (SAEs), and can store documents associated with the safety event that facilitate the generation and tracking of queries.
Open Drug Discovery Toolkit (ODDT) is modular and comprehensive toolkit for use in cheminformatics, molecular modeling etc. ODDT is written in Python, and make extensive use of Numpy/Scipy
Nautilus LIMS for Dynamic Discovery and R&D Environments is a highly flexible, easily configurable system that increases workflow efficiency, throughput and data reliability while simplifying administration, sample traceability and regulatory compliance.
American Gene Technologies (AGT) practices the art and science of genetic medicine. AGTrobust programs of discovery and drug development also include efforts on research and development of genetic medicines for treating Parkinsondisease and familial dysautonomia a rare, inherited orphan disease that is characterized by early onset blindness and other neurological problems. As priority programs move toward clinical testing, and as AGT continues to grow, these and other areas of investigation wil
Atomwise patented the first deep learning technology for structure-based small molecule drug discovery. This AI technology harnesses millions of data points and thousands of protein structures to solve problems that a human chemist would take many lifetimes to solve.
BioSymetrics' Augusta is a first of its kind software framework and coding language for Biomedical AI/Machine Learning applications that include drug discovery, precision medicine and value based care. Augusta contains over 300 code blocks and an iterative AI core to normalize any biomedical data type including chemistry(compounds), imagery (fMRI etc.) , genetics, EMR systems and more.
Aurora employs quantum mechanics, thermodynamics, and an advanced continuous water model for solvation effects to calculate ligand's binding affinities. This approach differs dramatically from scoring functions that are commonly used for binding affinity predictions. By including the entropy and aqueous electrostatic contributions in to the calculations directly, Aurora algorithms produce much more accurate and robust values of binding free energies.
Discovery Studio is BIOVIA's comprehensive predictive science application for the Life Sciences. BIOVIA Discovery Studio 2019 stands as BIOVIA's major release for predictive sciences and modeling and simulation in the life sciences
CCG is a leading developer and provider of Molecular Modeling, Simulations and Machine Learning software to Pharmaceutical and Biotechnology companies as well as Academic institutions throughout the world. CCG continuously develops new technologies with its team of mathematicians, scientists and software engineers and through scientific collaborations with customers.
Clinical Trial Outcomes Databases form a quantitative framework to leverage valuable external data, providing key development insights to maximize the probability of success for a new drug. Clinical Trial Outcomes Databases, accessed through our online interactive CODEx interface, provide comprehensive and up-to-date data on major therapeutic areas.
Compound Assist is much more than a "Cookbook" of formulas. It's a complete business package, from inventory control and ordering support to a print utility that generates machine-scannable bar codes for compounding medications.
FCS Express works hard to turn your flow cytometry data into results, so you don't have to. FCS Express can rapidly analyze vast amounts of data, with industry leading flow cytometry tools, but we recognize that is only the beginning of the scientific journey.
Automates time consuming and repetitive tasks during image analysis set-up. Increases reproducibility and detects complex phenotypes by eliminating the biased selection of handcrafted features. Saves time by quickly being re-applied in different experimental settings. Seamlessly integrates with Genedata Screener for image data analysis.
Gritstone Oncologygoal is to eradicate cancer by developing personalized immunotherapies to fight multiple cancer types. Gritstone Oncology is developing multiple immunotherapies designed to direct a robust immune response to neoantigens.
Over time, the pharmaceutical and biotechnology world has leveraged electronic data capture (EDC) and laboratory information management solutions to support their research and development efforts. It only makes sense that technology has evolved to provide the same type of process automation, data management, and other kinds of assistance to the drug development lifecycle.
Drug discovery software ensures that all calculations, determinations, and trials are thoroughly completed , without human error, and without potential bias. Drug discovery software also helps researchers, chemists, and scientists scale their efforts via process standardization, storage and duplication of data, accurate candidate identification, and alignment with risk and compliance measures. Drug discovery software significantly cuts down on the time, energy, and resources previously spent in developing new drugs. Drug discovery software makes it possible for scientists to positively impact the management of rising chronic diseases.
Key Benefits of Drug Discovery Software
The drug development process has historically been complex, expensive, and time-consuming. That’s not including all the quality management and regulatory aspects that newly developed drugs have to undergo to get to market. Drug discovery software leverages existing technology, for both the benefit of pharmaceutical companies that can make a profit off new drugs and for patients who can now have access to drugs that had not previously existed.
R&D productivity is significantly improved with drug discovery software. Automation is crucial to speeding up the drug development process but it also reduces the margin of human error via machine learning, simulations, and data-mining technology. Additionally, drug discovery software stops researchers from leaning so heavily on chemistry alone. Researchers can now take advantage of all the existing drug, assay, molecular, and protein information out there.
Time saved — Technologies and methods like machine learning services and artificial intelligence help scientists parse through massive data sets, which enables the rapid development and launch of new drugs to market. Instead of relying on chemistry alone to approve or deny drug development, scientists and labs can use computers and other computational methods to analyze and generate insight about the drug in development.
Automation — Tasks like high-content screening (HCS)—which automates the process to identify the kinds of target cells and ways substances can alter them—and high-throughput screening (HTS)—which sorts through existing compounds to narrow down the number of new drug candidates—used to be incredibly labor-intensive. The time that scientists had to spend waiting for the systems to search through existing drugs to find potential candidates used to be weeks, if not months. With automation, that time is reduced to mere hours. That means that R&D teams can focus more on tweaking and adapting drugs instead of waiting in limbo for approval.
Drug discovery software fulfills one particular need: automate (and thereby streamline and speed up) the drug development lifecycle. Accordingly, there is a very specific user demographic of drug discovery software:
R&D scientists — Researchers and scientists who work in the pharmaceutical industry and biotechnology laboratories rely on drug discovery software to become more productive, automate time-consuming tasks, and keep track of the work they have done so far in the lab.
Clinical trial organizers, managers, analysts — The near-final step of drug discovery is running it through clinical trials. While clinical trial organizers can rely on CTMS to take care of actual trial intricacies, they can depend on drug discovery software to reduce the time spent on screening for drug candidates.
Drug discovery solutions are constantly coming up with new and improved features, but the following features are fairly typical and standard across the board:
Prediction — Automated, predictive formulaic calculations that generate data, identify potential targets, determine interaction and activity predictions, and identify potential defects of developing drugs help speed up the drug discovery process.
Virtual screening — Scans and searches through libraries of chemical compounds and molecular structures against drug targets. Some virtual screening modules can be configured to select particular compounds. Virtual screening accelerates the drug discovery process by significantly reducing the potential cost to analyze, detect, and analyze the developing drug’s molecular dynamics and protein ligand structural components.
Docking — Predicts the binding affinity between two molecules, which is used during the drug design process. Additionally, regular molecular docking assessments are required for the product’s docking functionality to be as effective and accurate as possible.
Workflow management — Efficient and comprehensive workflow tools can speed up pharmaceutical process development. Workflow management features can include better data and information exchange, process standardization, and automation of IT processes.
Scale — Many of the technological innovations and discoveries that have been presented and discussed as positively impacting the drug discovery industry haven’t yet been implemented on a large scale. This poses a few problems, including unknown regulation complications and duplication problems.
Data management — Researchers and scientists may become overwhelmed by the sheer amount of data that can be generated once drug discovery processes are automated. While more data equals more context and use cases to refer to, more data also requires effective data management and analysis solutions for scientists to leverage the data.