Data-Driven
Pharma Innovation
Generating meaningful insights for Pharma Industry.
Improved data, improved care.
Generating meaningful insights for Pharma Industry.
Improved data, improved care.
Non-adherence alone costs the Pharma industry more than $600 billion in lost revenue each year. Pharmaceutical companies can benefit from engagement with their users and apply the insights for better results.
Through personalized user engagement, we can offers real-time insights into patient behavior. Filling in the gaps in data allows development of more effective and efficient interventions,
Then we apply Machine Learning algorithms to the combined data in order to generate insights for advanced pharmaceutical analytics and data-driven decisions making.
PharmaWise provides a platform for manufacturers to build real relationships with people by providing next generation engagement and support experiences. Manufacturers are able to gain valuable insights and deliver on “beyond the pill” engagement strategies.
PharmaWise’s platform keeps patients engaged and well-informed about their medication. Through this advanced, more connected engagement, PharmaWise provides pharmacists with insights that improve medication adherence, reducing medication related complications, increasing patient satisfaction, more frequent fills, an increase in average days on therapy.
PharmaWise analyzes streams of patient-generated data to predict treatment non-adherence to prevent it and maximize treatment outcomes and safety. We can help public and private healthcare providers achieve better treatment results and also work with preventative measures. For providers, this means accessing to information that can help improve care quality.
PharmaWise is your trusted and affordable solution for a wide range of clinical trials. It optimizes the chances of clinical trial success.
Towards the future Pharmacogenomics -Personalized Medicine
Everyone responds differently to treatment. By implementing genomic variance profiles, combining it with clinical outcomes of regimens, and adverse event information, we are moving towards creating valuable data for the future of personalized medication treatment.
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