AI/ML and Natural Language Processing (NLP) solutions
New era of individualized care, better patient health outcomes and improved ROI
- Develop targeted clinical trials and companion diagnostics using model-driven research and machine learning algorithms
- Build cloud infrastructure and data governance to ensure secure easy collection, flexible access, and intensive analysis
- Digitalize and analyze varied data from different sources, including images, PDFs, EHR, wearables and sensors, social medial, and more.
Unstructured data analyics
Apply artificial intelligence to leverage large quantity of new age and/or unstructured data, integrate it into meaningful insights and pharma and healthcare provider workflow , including:
- Rule-based text analytics
- Image and text file classification
- Scanned file recognition
- PDF conversion, and
- Facial recognition
Advanced sales analytics
- Apply machine learning algorithms to improve sales decision making on individual, management, and executive levels
- Achieve increased sales through giving pre-emptive and proactive next best actions on individual sales rep level
- Lower percentage of failed sales attempts through improving targeting and sales methods
- Develop visualization and CRM integration for commercial organizations
Wearable, real-time data analysis
- Deploy big data infrastructure and analytics to handle various new-age data sources to produce dashboards, reports applications and insights.
- Integrate process and outputs in client environment, smartphones or HCP’s Epic Systems.
- Utilize and contributing to open source resources such as Google APIs to develop real time applications to improve user/patient health, efficiency, and holistic systems.
AI/ML technology expertise
Axtria leverages advanced AI/ML algorithms to address multiple business needs. We have extensive experience with all core AI/ML technologies for life sciences, including:
- APACHE Spark
- Rapid Miner
- Google AI
- Azure Machine Learning
What it means and what it can do for the life sciences organizations
AI/ML techniques have found application across drug life cycle stages. Though slow to adopt, life sciences companies are leveraging AI/ML in newer fields with innovative approaches, and it has the potential to unlock several new avenues.
- Faster R&D and Drug discovery
- Early Diagnosis/detection
- Patient identification
- Precision medicine & personalized care
- Improved drug adherence
- Next best actions
- Real-time actionable insights for all stakeholders