Pharmaceuticals

Centralize Pharmaceutical AI/ML Strategies, Operations, & Insights To Increase Productivity, Reduce Costs & Facilitate Collaboration

AI is driving unprecedented productivity improvements across the pharmaceutical value chain—from the way drugs are developed, to stakeholder engagement and collaboration. Sense provides the pharma industry with one efficient AI IoT platform to accelerate and manage innovation, iteration, automation, and repeatability.

USE CASE

DRUG R&D ACCELERATION

Challenge

Drug research and development is a lengthy, complex, and costly process, with a high degree of uncertainty. Less than one percent of projects are successful. The entire process, from early research to drug approval, can take 12-15 years and costs average in the billions.

Solution

AI IoT for drug R&D provides pharmaceutical companies with cost- and time- saving automation and efficiency making discovery of new drugs cheaper, quicker and more effective. Sixgill AI Services combined with the Sense platform assist with data fusion for multi-data source input to AI/ML solutions. A broad array of solutions is possible and include pattern identification in large volume of data as well as initial screening of drug compounds to predict the success rate of a drug.

USE CASE

CLINICAL TRIAL OPTIMIZATION

Challenge

Many drugs fail in the clinical trial phases. However, device technology has evolved to the point that it is now possible to collect a vast array of physiological data, sleep, activity, and symptomatic data and combine new technologies to monitor trial participants remotely. Efficient and effective management of this data for analysis is needed for digital trial success.

Solution

With Sense, device management, data collection, data fusion/preparation, and ML model training and iteration can provide foundational, centralized knowledgebase for clinical trials and facilitate collaboration across stakeholders. AI solutions can include predictive analytics for target identification and drug repurposing. Models can also be trained to assist with recruitment and retention activities; for example, finding the right candidates at a faster rate to accelerate R&D timelines. Integrated real-time alerting based upon trial, data, or participant-specific criteria provides clinical investigators and teams with immediate, real-world knowledge to ensure wellbeing of patients and keep trials on track.

USE CASE

CLINICAL TRIAL OPTIMIZATION

Challenge

Many drugs fail in the clinical trial phases. However, device technology has evolved to the point that it is now possible to collect a vast array of physiological data, sleep, activity, and symptomatic data and combine new technologies to monitor trial participants remotely. Efficient and effective management of this data for analysis is needed for digital trial success.

Solution

With Sense, device management, data collection, data fusion/preparation, and ML model training and iteration can provide foundational, centralized knowledgebase for clinical trials and facilitate collaboration across stakeholders. AI solutions can include predictive analytics for target identification and drug repurposing. Models can also be trained to assist with recruitment and retention activities; for example, finding the right candidates at a faster rate to accelerate R&D timelines. Integrated real-time alerting based upon trial, data, or participant-specific criteria provides clinical investigators and teams with immediate, real-world knowledge to ensure wellbeing of patients and keep trials on track.

USE CASE

MEDICAL IMAGING

Challenge

Medical imaging is at a tipping point for technological transformation. There has been a massive increase in demand for cross-sectional imaging (CT and MRI). Medical images are becoming more complex, and at the same time there is a shortage of trained, experienced radiologists and health systems simply cannot recruit and train radiologists quickly enough to keep up with demand. These factors, combined with budgetary restraints made even more drastic due to the pandemic, are posing great challenges across pharmaceuticals and healthcare sectors.

Solution

Sixgill custom ML models used with the Sense platform process information faster than humans and enhance human-led clinical analysis and decision making by providing accurate contextualized information quickly and cost-effectively. By implementing the Sense platform for ML life cycle management for medical imaging, organizations increase efficiency and accuracy, and eliminate the significant burdens of device and model management system development. With Sense, pharma innovation teams, data scientists, as well as clinicians can devote their expertise to research, treatment development and patient outcomes.

Whether you need our Enterprise AI services to build custom models or have the team to build or upload models and manage them within Sense, please let us know how we can help solve your use case requirements and the needs of your business.

Contact us today to request a demo of Sense.