Intelligent Healthcare Analytics and AI in Pharma
Biotech Digital Transformation
Biotech Digital Transformation Project
Stage 1: Data Lake Creation
We deal with the following:
- Multiple diverse Data Sources
- Multiple subsidiaries (e.g. Data providers)
- Availability of Data in multiple geographies (US, Europe, Australia, etc.)
- Data Lake compliance with GDPR and HIPAA
- Availability of Data Lake for Data Analysts to work within first 4 weeks from the beginning of the project
Stage 2: Ingestion and Data Quality Check
- All Data Sources are supported for processing
- All data (including raw data) is ingested into the pipeline for Data Quality and Validation
- All processed data is placed into the Data Lake available for immediate analysis
- Ingestion is implemented into the pipeline during the POC
Stage 3: Processing, ML and Analysis
- Valid Data after the ingestion is processed by the Step Functions and AWS Glue (this includes any ML transformations needed)
- All Processed Data is available in Data Lake for immediate analysis
- All Processed Data is uploaded into the Data Warehouse and available for all Data Analysts
- The whole pipeline is fully automated and built with multiple error retry mechanisms to be self-sufficient
- Logging and monitoring including notifications mechanism to be implemented during Stage 3
- Architecture supports scalability to handle any load required
- Stage 3 is complete in 8 to 12 weeks after the POC
Stage 4: Visualization and Reports
- All Processed Data is uploaded into Redshift for Analysis and Visualization
- Redshift access can be granted to any subsidiaries (e.g. stakeholders or third-party subsidiary investors that need the access to data)
- Visualization and Reports are built on top of Redshift tables with PowerBI
- Stage 4 is expected to be complete within the same data frame as Stage 3 (8 to 16 weeks after the POC)
We deal with the following:
- Multiple diverse Data Sources
- Multiple subsidiaries (e.g. Data providers)
- Availability of Data in multiple geographies (US, Europe, Australia, etc.)
- Data Lake compliance with GDPR and HIPAA
- Availability of Data Lake for Data Analysts to work within first 4 weeks from the beginning of the project
- All Data Sources are supported for processing
- All data (including raw data) is ingested into the pipeline for Data Quality and Validation
- All processed data is placed into the Data Lake available for immediate analysis
- Ingestion is implemented into the pipeline during the POC
- Valid Data after the ingestion is processed by the Step Functions and AWS Glue (this includes any ML transformations needed)
- All Processed Data is available in Data Lake for immediate analysis
- All Processed Data is uploaded into the Data Warehouse and available for all Data Analysts
- The whole pipeline is fully automated and built with multiple error retry mechanisms to be self-sufficient
- Logging and monitoring including notifications mechanism to be implemented during Stage 3
- Architecture supports scalability to handle any load required
- Stage 3 is complete in 8 to 12 weeks after the POC
- All Processed Data is uploaded into Redshift for Analysis and Visualization
- Redshift access can be granted to any subsidiaries (e.g. stakeholders or third-party subsidiary investors that need the access to data)
- Visualization and Reports are built on top of Redshift tables with PowerBI
- Stage 4 is expected to be complete within the same data frame as Stage 3 (8 to 16 weeks after the POC)
Areas of Expertise
Predictive Analytics & Healthcare Delivery Enhancement
Meet unique patients’ needs and enhance healthcare delivery with stellar predictive analytics solutions.
Diagnostics can be easier with big data analysis and machine learning. Use our ML-based predictive models for the automatic detection of anomalies in patient clinical data. Analyze the results to adjust the intended treatment plan and navigate medicine risks like adverse reactions and medication side effects.
Prevent chronic diseases and improve patient outcomes. Analyzing patient-generated data, you can predict disorders like diabetes or heart disease. Predictive analytics tools will help you identify high-risk patients and predict their future outcomes. Make personalized predictions and treatment plans reducing the risk for hospitalization.
OCR & Healthcare Business Processes Optimization
Tired of managing paper documents? Make a smooth transition from paper to digital with our custom OCR solutions. Optimize healthcare business processes through data capture, retrieval, and extraction. With OCR solutions it’s easy to digitize all kinds of healthcare documents including patients’ records, prescriptions, claims, reports, invoices, etc.
Allow automatic data entry and smooth health data transfer between organizations. Deploy bespoke OCR software into your hospital for laborious tasks to save time and money.
Develop an AI pharma EHR for smooth clinical predictions and analytics. Allow for smart workload forecasting and resource management, medication demand. Get insights to promote better patient outcomes with artificial intelligence in pharmacy.
NLP for Personalised Care
Analyze medical documents to predict conditions. Use NLP to extract data from clinical documents for intelligent diagnostics.
Get to know your clients better with NLP API software. Find out who your target audience is–age, gender, interests, specifics, etc. Use the data to better market yourself, keep old customers, and attract new ones.
Analyze comments on social media about customer experiences to see how they rate your services. Score comments into people, places, and services to see if your patients are happy with your brand or there’s room for development. Use the insights to improve the overall quality of services and care.
Computer Vision for Physical Therapy Transformation
Transform physical therapy with AI health solutions like pose estimation. Implement pose estimation models into your app to track, estimate and provide therapeutic feedback on patient joints and posture in real time. Bring guidance on doing the exercising and motivation to carry on. Check the progress of the patient over the course to navigate treatment protocol.
Сomputer Vision for Authentication Procedures
Today there is a growing demand for different types of personnel authentication tools & technologies for both online and in physical systems.
With our robust computer vision algorithms, it’s easy to collect and store facial data. Use the data to verify personnel and provide or ban access to certain areas.
Сomputer Vision for Customer Services Improvement
Want to better market your hospital but afraid of being salesy? Impress your patients with Face Recognition Greeting Tool. Recognize and greet patients by the name as soon as they enter the hospital.
Integrating our tool into your infrastructure, you’ll deliver great customer service and boost patient retention and referrals with ease.
Сomputer Vision for Medical Image Analysis
Detect and identify diseases with medical image analysis powered by Machine Learning. Get meaningful data insights for on-time anomaly detection and early disease intervention based on clinical imaging. As a result, streamline the workflow of the radiologists and get better patient outcomes.
AI and Big Data for Pharma
- Advanced RWE Analytics
Uncover insights from advanced real-world evidence across the whole pharma value chain to inform R&D decisions and improve trial design, achieve better patient access, implement smart targeting and data-driven commercial activities, as well as improve pharmacovigilance to be able to respond promptly to adverse events and unmet patient needs.
- NLP: Scientific Literature and Patents Analysis
Implement artificial intelligence in pharmacy in a safe and controlled way with AI. Use custom NLP solutions for data mining and analysis including smart collection, labeling pharma studies, highlighting relevant information to your queries, and enhancing modeling.
- AI Drug Development and Analytics
Uncover opportunities in drug development with AI. Produce drug-like molecules, optimize for binding affinity to your protein target, choose most chemically promising leads for further validation using generative modeling, reinforcement learning, and evolutionary algorithms.
Improve your QSAR prediction of ADMET сompound properties with Graph Networks, it’s easy to approximate ADMET properties from the 3D compound structure or SMILES-like molecular representations.
- Cell Image Capture and Analysis
Want to make cell analysis easier? Implement automated image capture and analysis for cell imaging. With that, you’ll detect anomalous tissues, segment various types of cells, detect cancerous tissues, and what is the effect of a drug.
- Big Data Analytics for Pharma Companies
With custom Big Data solutions, you can easily manage the wealth of data. Gather, store, transit and extract data in a click. Use emerging pharma tech to run analytics and machine learning models with ease. Get the most of data analytics to ensure the success of your pharma company.
Uncover insights from advanced real-world evidence across the whole pharma value chain to inform R&D decisions and improve trial design, achieve better patient access, implement smart targeting and data-driven commercial activities, as well as improve pharmacovigilance to be able to respond promptly to adverse events and unmet patient needs.
Implement artificial intelligence in pharmacy in a safe and controlled way with AI. Use custom NLP solutions for data mining and analysis including smart collection, labeling pharma studies, highlighting relevant information to your queries, and enhancing modeling.
Uncover opportunities in drug development with AI. Produce drug-like molecules, optimize for binding affinity to your protein target, choose most chemically promising leads for further validation using generative modeling, reinforcement learning, and evolutionary algorithms.
Improve your QSAR prediction of ADMET сompound properties with Graph Networks, it’s easy to approximate ADMET properties from the 3D compound structure or SMILES-like molecular representations.
Want to make cell analysis easier? Implement automated image capture and analysis for cell imaging. With that, you’ll detect anomalous tissues, segment various types of cells, detect cancerous tissues, and what is the effect of a drug.
With custom Big Data solutions, you can easily manage the wealth of data. Gather, store, transit and extract data in a click. Use emerging pharma tech to run analytics and machine learning models with ease. Get the most of data analytics to ensure the success of your pharma company.
Services We Provide
Consulting
Have a business problem? Use our consulting services, strong tech expertise, and experience in the healthcare IT solutions market.
Healthcare IT Solution Development
Not satisfied with packaged healthcare software available on the market? Let our tech team build web or mobile solutions specifically for your needs.
Healthcare Analytics and Business Intelligence
Want to get insights into clinical care, administration and costs? Make use of analytics and BI tools to track KPIs and readjust your strategies.
Testing and QA
Document processing systems, AI apps for mental health or physical therapy – we’ll make sure your healthcare IT solution runs smoothly.
Value You Get
Why Partner with InData Labs?
80 + ExpertsOur data scientists and engineers are shaping modern medical technologies. We’re experienced in digital healthcare and MedTech solution development.
Industry-FocusedWe stay on top of the industry trends. We understand the needs of our clients and aid them with AI-based solutions that solve their problems.
ReliableWe prioritize our clients. Our goal is to help them reach new heights by innovating their businesses with AI.
Customer Success
