Pharma & Biotech
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Accelerate data integration from multiple sourcesAccelerate drug discovery by automating research stages and data integration and analysisAnalyse biomarkers such as genes for medical potentialAnalyse clinical outcomes to adapt clinical trial designAssist physicians by diagnosing and providing the latest medical information about rare conditionsAutomate preparation of data for inclusion in analytics platformAutomate protection of privacy in mapping data generation processesCreate personalised food menu and dietDiagnose known diseases from scans, images, biopsies, audio and other dataEnable genome sequencing for personalised cancer treatmentEnhance search process for new molecular structuresIdentify and manage potentially fraudulent activityIdentify and validate a molecule to target with a drug compoundIdentify candidates for trial recruitmentIdentify creature characteristics to assist in disease controlIdentify existing drugs for improvementIdentify new therapeutic uses for existing drugsIdentify target patient subgroups that are underserved or underdiagnosedLeverage molecule database with metabolic stability data to elucidate new stable structuresModel out hypothesis of drug impactMonitor patient outcomesMonitor patient prescription complianceOptimise clinical trial design including patient selectionOptimise experimental efficiency through refining research process and operationsOptimise medical product launch strategy based on past launch or market dataOptimise pricing strategy for drug portfolioOptimise resource allocation in drug development using disease trends and other dataPredict biomarkers for drug box labellingPredict drug demand in different geographies for different productsPredict outcomes from fewer or less diverse experiments to reduce research costs and time to marketPredict personalised health outcomes to recommend individual treatment approachPredict potential adverse effects when drugs taken are combinedPredict target drug resistancePredict the behaviour of CRISPR for gene editingPrioritise research and development projectsProduce drugs for scaled testingRe-examine data from historic research to discover new applicationsReduce side effects by collating patient data and optimising processesScale and support data management and monitoringSpecify approach to crop growth based on individual plot characteristics and real time dataTrack and predict disease vector in general population
Pharma & Biotech Case Studies
Abbvie achieves 90% cumulative medication adherence among patients with schizophrenia using image recognitionAstraZeneca improves internal management of its global data sources through organisation, search and information extraction using an AI platformAstraZeneca plans to crack down on online sale of counterfeit drugs in China using machine learning and natural language processingBERG is attempting to identify genetic predisposition to certain conditions using machine learning with promising Phase I study resultsBERG is developing targeted cancer drugs using machine learning with promising Phase I study resultsBayer aims to spot drug-associated side effects earlier with the use of machine learning, RPA and natural language processingCambridge researchers develop a system to analyse cancer research papers to discover previously unexplored molecular biology linksDana Farber Cancer Institute accelerates clinical trial recruitment by using machine learning for genome mapping to identify best candidatesDayTwo improves blood sugar management through personalised diet recommendations based on gut microbiome analysis using machine learningDeepMind develops a highly accurate machine learning method for predicting protein structuresGlaxoSmithKline (GSK) plans to accelerate drug discovery as well as new applications for existing drugs using machine learningGlaxoSmithKline (GSK) plans to reduce drug discovery to trial time from six years to 12 months using machine learning models to predict molecular behaviourHealx''s scientist predicts effectiveness of combinations of antibiotics using machine learningMIT scientists develop system that crowdsources data to speed up drug discovery using neural networksNovartis researchers train algorithm to identify different cell types to spot cancer in scansPeptone accelerates protein research for drug discovery with a machine learning derived databasePfizer identifies new potential cancer treatments using IBM WatsonPharmaceutical company identifies warnings for non-Hodgkin’s lymphoma patients requiring change of treatment using machine learningResearchers at Macau University of Science and Technology develop a new model for disease classification in cases of limited labelled data with ~90% accuracy by combining logistic regression and semi-supervised learningResearchers at Stanford University develop an approach for modeling polypharmacy side effects with graph convolutional networks outperforming baselines by up to 69%Researchers at University of Lisbon accelerate drug discovery with the use of machine learningResearchers at the University of Glasgow develop platform to locate new molecules using machine learningRoche plans to reduce time-to-market for oncology medicine by streamlining clinical trial process with machine learningSanofi Pasteur plans to make vaccines more effective by assessing biomarkers of influenza vaccination outcomes with machine learningTakeda and ConvergeHEALTH aim to better understand how treatment-resistant depression responds to medication using deep learning modelsTakeda partners with Numerate to improve pharmaceutical clinical trial efficiency by using AI to inform design decisionsThe Good Doctor Pharmaceutical Group''s farm achieves manufacturing efficiency in breeding cockroaches for medicinal purposes through an AI-powered smart systemUniversity of Glasgow researchers predict virus reservoir hosts with 83.5% accuracy and provide hypotheses about unknown viral vectors