Digital Transformation Solutions for Pharmaceutical Companies

Increase quality and improve delivery.
Aridhia Informatics simplifies healthcare analytics for clinical researchers using Pivotal solutions.
Watch Video

Pharmaceutical Companies Trust Pivotal's Cloud-Native Platform,
Data Solutions and Pivotal Labs.

• Diagnoses

• Cures

• Treatments

• Disease prevention

• Medical technology

Use Cases
Drug delivery

Use models to gain insights into drug development processes. Avoid the loss of products that do not meet quality standards. Reduce workloads on employees and demonstrate how statistical tools can identify data entry errors. Allow your biotech or pharmaceutical company to take corrective steps early.

Regulatory compliance

Overcome challenges related to revising compliance and governance infrastructure to meet regulatory standards in a timely manner.

Clinical research

Arrive at conclusions faster. Analyze data distributed across health organizations (e.g., EPA, FDA, biotech labs, CDC, instrument vendors, drug labs, patients, pharma companies, contract research organizations, universities, and hospitals) at the same time.

Drug innovation

Repurpose drugs, identify potential companion diagnostics, target population treatment and achieve remote patient monitoring and disease management.

“Pivotal was able to take our vision and create something far beyond our expectations.“
Sze-Ping Wong
Product Manager, Crescendo Bioscience

Benefits to Your Enterprise

Launch new products faster

Discover new agile processes to launch products faster, scale resources on demand, and adapt to changing requirements and regulations. Streamline application development, deployment and operations on a centrally managed platform as a service for public and private cloud.

Model possibilities

Predict the potency of cures and gain insights into the manufacturing process to fine-tune production. Embrace paired programming to conduct A-B testing in a neutral environment.

Reduce costs

Drive down drug-related costs by reusing expensive sets of data. Reduce the amount effort and research required for drug breakthroughs. Introduce personalized medicine while keeping the cost of manufacturing down in order to remain profitable. Reengineer processes to enable more cost-effective delivery of drugs to patients on different continents.