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A scientist at a microscope

Life Sciences
Use Cases

Each part of a life sciences company has its own problems, data, and regulators. Start with your department.

Life Sciences overview

19 use cases

Search use casesAll departments

Clinical trials

2 use cases

Clinical trial and supply integrity monitoringAI clinical trial and supply integrity monitoring flags unusual patterns in site data, sample distribution, and supply movements, with reasons behind each flag, for your monitors and compliance teams to review.Clinical trial site selectionPredictive models that use past trial performance and feasibility data to estimate which investigator sites are likely to enroll the patients a study needs, on time.

Commercial

5 use cases

Optimizing promotional spend and budget by channelAI models how each promotional channel, region and brand responds to spend, so your commercial team can set the next budget from evidence instead of last year's split.Personalized patient support programsAI for personalized patient support programs groups patients by shared needs and flags who may stop a therapy early, so support teams reach them in time.Pharma field force performanceAI agent performance scores pharma field reps' opportunities and suggests next best actions from CRM and call data, cutting the manual entry that keeps adoption low.Physician targeting for a product launchAI product launch physician targeting ranks the healthcare professionals whose patients fit your newly approved therapy, so your commercial and medical teams reach the right prescribers first.Provider scoringLicensed prescribing and engagement data rank healthcare professional accounts by how closely their patients fit approved indications, so field and medical teams plan coverage from one explained score.

Research

4 use cases

Biomedical literature and knowledge graph synthesisAI biomedical literature synthesis reads publications and your internal reports, maps the genes, targets and findings they describe, and answers your scientists' questions with a citation for every statement.Gene mutation risk scoringGene mutation AI scores a patient's genomic and phenotype profile for genetic risk and ranks the genes and pathways that drive it, for your research and clinical teams.Mechanism of action prediction for drug screeningMachine learning that estimates how a compound acts on biology from gene expression and cell viability data, so scientists can prioritize hits sooner.Patent landscape and competitive intelligenceA patent landscape and competitive intelligence assistant searches patents, trial registries and publications, groups what it finds and answers your team's questions with a citation for every statement.

Safety

4 use cases

Biomedical literature and knowledge graph synthesisAI biomedical literature synthesis reads publications and your internal reports, maps the genes, targets and findings they describe, and answers your scientists' questions with a citation for every statement.Classifying patient-reported drug reviewsAI reads what patients write about a drug in reviews and sorts each one as effective, ineffective or adverse, routing every possible adverse mention to a person for review.Drafting safety reports and submission sectionsAI drafts cited sections of periodic safety reports and regulatory submissions from your approved sources, and checks a package for gaps, for a qualified person to sign.Pharmacovigilance case intake and signal detectionDocument reading and agents that turn incoming adverse event reports into structured cases, suggest coding terms for your coders to confirm, and surface possible safety signals in free-text narratives.

Supply chain

5 use cases

Pharma inventory and out-of-stock risk predictionMachine learning on demand, inventory and order data that flags which pharma products are likely to run short, forecasts lead times and safety stock breaches, and suggests reorders planners approve.Predictive maintenance for pharma manufacturingAI predictive maintenance for pharma manufacturing uses sensor, batch, and maintenance data to predict which production equipment is likely to fail, and when, so engineering can act before a failure stops a batch.RFP and procurement automationAI RFP and procurement automation reads your RFP and every vendor proposal, compares them on scope, pricing and terms, and answers evaluation questions with a citation to the source.Supplier document validation against the ERPSupplier document validation reads supplier contracts, purchase orders, invoices and certificates of analysis, checks each value against your ERP, and sends only the mismatches to a person.Supplier risk scoringAn AI supplier risk model uses delivery, quality and commercial history to predict which pharma suppliers are likely to miss a delivery or fail a quality check.

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