Pharmaceuticals & BioTech

SFL Scientific is working with the worlds leading for Pharmaceutical and Biotech companies to address their most significant challenges with machine learning and data science.
Pharmaceuticals & BioTech


SFL Scientific has expert domain knowledge and an intimate understanding of personalized medicine, -omics, drug and clinical data, deploying neural networks, and novel solutions to R&D type problems.

Our Custom Strategy

Natural Language Processing

Statistical models, data mining, database management

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Predictive Analysis/Time-Series

It's critical to develop a plan to integrate the model, not just make a predictive score

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Data Engineering

Designing data architecture and best practices for secure, efficient, and cost-effective data and IT systems.

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We Work with Top Pharmaceutical & BioTech Companies

Use Cases

AI Use Case for Pharmaceuticals & BioTech

SFL Scientific data scientists are in a position to help streamline operations with domain knowledge and an intimate understanding of personalized medicine, -omics, drug and clinical data, deploying neural networks and novel solutions to R&D type problems.

Biomarker Analysis for Clinical Trials

Depression is one of the leading causes of disability worldwide, with more than 300 million people affected. Depression is misdiagnosed and only about half of patients respond effectively to SSRI treatments. Therefore, the ability to identify patients accurately and create automated tools may significantly improve outcomes and advance therapeutic procedures.

Deep Learning

Patient Forecasting & Supply Chain

Develop algorithms to forecast patient demand across blood draw and clinical test sites for various tests, factoring weather, holidays, geography, and other factors predicting services & associated demand.

Machine Learning

Investor Relations Modeling

Develop comprehensive models using historical stock trading data to determine how specific investors react to the launch of new drugs or the expansion of market approved drugs.

Machine & Deep Learning

Document Pharmacovigilance

Developed an entity extraction engine that automatically extracted key medical terms and dependencies from clinical and drug documents in eight European languages.


Hybrid Big Data & AI Platform Development

Engineered and implemented an end-to-end data science platform across R&D areas of the company. Developed cloud architecture, services, data lakes, compute provisioning, & containerized deployment.

Data Engineering & DevOps

Named Entity Recognition Pipeline

SFL Scientific performed an exploratory data analysis and developed custom NLP-based text extraction models to examine medical prescription data. The information contained doctor, patient, and historical script attributes such as dosage, frequency, supply, etc.

Deep Learning

Use Cases

Data Science and AI Use Cases in Pharmaceuticals & Biotech

SFL Scientific creates opportunities pharma and biotechnology organizations to deliver on ground-breaking drug discovery, diagnostic support, clinical trial and operational outcomes.

Labs and Production

  • Production line Tracking
  • Computer vision for QC
  • Sample Processing
  • Event Monitoring

Information Management

  • Custom OCT
  • Document Classification
  • Automated Review
  • Speech & Audio Analysis

Research & Development

  • Biomarker Analysis
  • Digital Trials
  • Patient Adherence
  • Precision Medicine

Clinical Trials

  • Measuring Drug Response
  • Site Enrollment Prediction
  • Trial Monitoring
  • Risk & Outlier Handling
  • Trial Risk/Performance

Creating a roadmap from concept to deployment

Most Pharmaceutical manufacturers know it’s not a question of whether or not to deploy AI solutions, but a matter of when and where to start.

Our US-based team of data scientists, consultants and engineers can guide you through the process of driving real business value with AI. We will work to understand your AI business cases,  identifying unique areas of innovation that require further research with proof of concept through building models and deploying sustainable, performant AI business applications at scale.

Team brainstorms with sticky note exercise
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We’d like to work with you to understand your unique AI challenge from modernizing legacy platforms to developing new AI solutions. Technology moves fast, let’s build sustainable solutions.

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