VIVO

Clinical trial insights platform

Advance precision medicine: Multi-modal analysis of clinical trial data

VIVO enables biopharma sponsors to accelerate clinical trial data science analyses to maximize drug development success.

VIVO enables innovative approaches such as AI, ML, and deep computational phenotyping to identify and validate biomarkers to aid patient stratification, increase knowledge of disease progression, and identify enriched groups of responders for future recruiting strategies.

VIVO-Bio - Find signal in Molecular
Find the most predictive biological signals

VIVO applies robust bioinformatics workflows to tie biological pathways to outcomes. Ingest and merge multi-omics and biochemical datasets to confidently identify predictive biomarkers and optimize modeling performance.

VIVO-Digital - Find signal in Digital
Gain value from all digital data sources

VIVO stratifies patients and quantitatively assesses therapeutic response and provides key insights into cognitive and emotional response. VIVO supports pathology and radiology images and a wide range of digital biosensor data including EEG, ECG, video, voice, and language/sentiment analysis of transcripts.

Accelerate data science
Enable rapid experimentation

VIVO is an end-to-end pipeline transforming raw data to final biological insight, designed to allow maximum flexibility to experiment and modify workflows with flexible functionalities for biology.

Case studies related to the VIVO platform

Data science strategy for biomarker discovery

Learn More

Voice and video analytics for pediatric mental health

Learn More

A scalable data science platform to orchestrate clinical trial analysis workflows and analyze results

Learn More

Related blog posts

The Case for Video AI in Telemedicine

Read our top three use cases on the integration of AI video analytics to significantly raise the value of both Telemedicine-based care and Distributed Clinical Trials.

Learn More

A Better Facial Emotion Recognition Model

Major cloud service providers offer off-the-shelf emotion prediction APIs, but accuracy and interpretability often fail to meet the needs of our clients. Read how our team developed a new approach to predict emotions from video. Here we describe the model building process, its current performance, and future considerations.

Learn More

Eliminating Racial Bias in AI/ML: Solving the Training Data Problem

Learn about the approach and impact of the model we built to predict skin tone from face images and videos using a unique combination of computer vision and machine learning to help organizations monitor for racial biases in large datasets.

Learn More