The Life Sciences and Health Care AI Dossier

Digital Data Flow for Clinical Trials

Use cognitive automation to integrate trial data from multiple systems, populate standardized digital data elements, and generate trial artifacts such as case report forms and study reports.

Drug Manufacturing Intelligence

Use algorithmic models and sensor data to maximize factory yield and productivity by predicting manufacturing deviations and proactively suggesting corrective actions.

Drug Marketing Omnichannel Engagement

Use machine learning models to predict the best ways to engage with patients and health care professionals (HCPs)—and to optimize marketing spend across media channels.

Voice of the Patient Insight

Use AI to analyze patients’ and HCPs’ social media feedback, complaints, and adverse events — generating insights that can improve product design, packaging, and educational materials.

Proactive Risk and Compliance

Use AI to automate the analysis and aggregation of data when identifying risk and compliance issues—recommending the next best action and possible mitigation methods.

Patient Engagement

Use AI to improve every aspect of patient engagement, from scheduling appointments and accessing medical records, to communicating with health care staff and care coordination teams.

Health Care Revenue Cycle Optimization and Efficiency

Use AI to automate claims submission and payment for pre-care, day-of-care, and post-care activities.

Computer Assisted Diagnosis

Use AI technologies to diagnose medical conditions more efficiently and accurately.

Precision Medicine & Personalized Health

Use predictive insights to proactively diagnose, prevent, and treat a future illness based on an individual’s lifestyle, real-world environment, biometric data, and genomics

Hospital Management

Use predictive AI to forecast peaks and valleys in patient volume and then adjust hospital staffing and resource levels accordingly.

Biomarker Discovery

Using AI to analyze life sciences data and identify novel biomarkers through pattern recognition.

Synthetic Biology

Using AI to engineer new synthetic life forms that serve useful purposes.

Virtualized Drug Discovery Lab

Using AI, quantum physics, cloud computing, and a molecule database to create a “digital twin” for simulating the activity of potential new drugs.

Self-healing Supply Chains

Using AI to create optimized, proactive supply chains that can automatically address unexpected disruptions.

Digital Health Care Providers

Using AI to help medical professionals provide a wide range of health care services.

Predictive Behavioral Model

Using AI to select clinical trial participants

Digital Pathology

Using AI to increase the speed and accuracy of disease diagnosis.

Patient Vitals Monitoring

Using AI to analyze and identify anomalies in patient vitals data captured through wearable devices.

Medication Compliance & Remote Patient Monitoring

Using AI image recognition and smartphones to remotely monitor outpatient behavior and whether patients are taking their medications as directed.

Diagnostic Image Enhancement in Radiology

Using AI technologies to enhance and analyze radiological images.