Leveraging Machine Learning
to Enhance Productivity in
the Life Sciences Industry

Learn how life sciences firms can use ML to favorably impact R&D productivity, clinical efficacy, and supply chain efficiency.

Pharmaceutical and
BioTech

Bringing advanced analytics and machine learning to operations, R&D, and marketing

Improving productivity and outcomes using AI

R&D & Clinical

We can help build AI models to improve clinical trials and process large datasets in drug discovery.

Manufacturing and Supply Chain

We can help optimize your supply chain and manufacturing processes, prevent stock outs, improve QA/QC, and avoid downtime.

Sales & Marketing Commercialization

We can help increase engagement across your sales and marketing channels.

Enter a New Age of Innovation and Productivity

We help life sciences companies take advantage of data from big data repositories containing patient health records, human genome data, and other information, to the huge volumes of data generated daily by the commercial side of your operation including  sales, distribution, and marketing information.

By using advanced cloud computing platforms and customized ML algorithms to R&D and clinical trials, manufacturing, supply chain operations, and commercial sales and marketing.

Use cases

New or Repurposed Drug Therapies

Using custom-built ML algorithms to identify new patterns and trends that can lead to new therapies or product extensions. Identify new biomarkers that improve diagnoses or re-evaluate previously failed therapies to see if they are actually effective for a more narrowly-defined target population.

Optimized Product Portfolios

Apply ML-enabled analysis to product development pipelines to assess potential trial outcomes across the product portfolio. Validate targets much earlier in the process, improve investment decisions and avoid ineffective R&D and clinical trial spend around therapies.

Stockout Prevention

Stockouts in clinical settings not only affect the bottom line with reduced sales and higher generic substitutions, they can also delay medical procedures that impact patient safety. That’s why we help drug dispensers with ML-enabled automation and visual inspection technology to accurately predict stockouts and ensure timely fulfillment to prevent them.

Sales Pipeline Expansion

Maximize the value of your sales activities with predictive sales forecasting that continuously analyzes past and current pipeline data to assess future sales performance. Assess the lifetime value of customers and propensity to churn.

Improved Trial Efficiency and Outcomes

Optimize clinical trial design and avoid committing extensive investments in personnel, patients, and resources. Run data-driven “virtual” clinical trials to pre-determine outcomes and test different hypotheses. Combine genomic data with electronic health records (EHRs) to establish an ideal patient profile that better fits the drug’s target population, so clinical trials won’t fail due to poorly-defined eligibility requirements.

Improved Value and Uptime of Critical Equipment

Avoid costly downtime of mission critical laboratory and manufacturing equipment by combining predictive maintenance algorithms with Internet of Things technology or edge computing to monitor and analyze machine sensor data in real-time. Ensure proper machine calibration, predict equipment failure, and maximize the lifetime of parts by replacing or servicing them only when necessary.

Marketing Campaign Effectiveness

Monitor campaign performance across your entire media landscape. Gain deeper insight into patient and physician interactions with advertising and messaging activities including interactions on social medical platforms. You can use sentiment analysis to better understand user activity and ad performance in terms of cost-benefit and opportunity conversion, as well as know when and how to engage with users directly to seize new opportunities.

New or Repurposed Drug Therapies

Using custom-built ML algorithms to identify new patterns and trends that can lead to new therapies or product extensions. Identify new biomarkers that improve diagnoses or re-evaluate previously failed therapies to see if they are actually effective for a more narrowly-defined target population.

Improved Trial Efficiency and Outcomes

Optimize clinical trial design and avoid committing extensive investments in personnel, patients, and resources. Run data-driven “virtual” clinical trials to pre-determine outcomes and test different hypotheses. Combine genomic data with electronic health records (EHRs) to establish an ideal patient profile that better fits the drug’s target population, so clinical trials won’t fail due to poorly-defined eligibility requirements.

Optimized Product Portfolios

Apply ML-enabled analysis to product development pipelines to assess potential trial outcomes across the product portfolio. Validate targets much earlier in the process, improve investment decisions and avoid ineffective R&D and clinical trial spend around therapies.

Improved Value and Uptime of Critical Equipment

Avoid costly downtime of mission critical laboratory and manufacturing equipment by combining predictive maintenance algorithms with Internet of Things technology or edge computing to monitor and analyze machine sensor data in real-time. Ensure proper machine calibration, predict equipment failure, and maximize the lifetime of parts by replacing or servicing them only when necessary.

Stockout Prevention

Stockouts in clinical settings not only affect the bottom line with reduced sales and higher generic substitutions, they can also delay medical procedures that impact patient safety. That’s why we help drug dispensers with ML-enabled automation and visual inspection technology to accurately predict stockouts and ensure timely fulfillment to prevent them.

Marketing Campaign Effectiveness

Monitor campaign performance across your entire media landscape. Gain deeper insight into patient and physician interactions with advertising and messaging activities including interactions on social medical platforms. You can use sentiment analysis to better understand user activity and ad performance in terms of cost-benefit and opportunity conversion, as well as know when and how to engage with users directly to seize new opportunities.

Sales Pipeline Expansion

Maximize the value of your sales activities with predictive sales forecasting that continuously analyzes past and current pipeline data to assess future sales performance. Assess the lifetime value of customers and propensity to churn.

Customer Successes

Thought Leadership

Check out our recent blogs and videos on best practices and implementation approach to help the healthcare community.

Let's Chat

We’re ready to help you seize the advantage with Machine Learning in Healthcare and Life Sciences.

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