Year in Review

1. 2024: Year in Review

2. Identifying and Studying Hard-to-Characterize Patients

3. Completing the Patient Journey with AI & Real-world Data

4. Automating Prospective and Retrospective Studies & Registries

2024 In Review

In 2024, AI continues to revolutionize drug development in the broader pharmaceutical landscape. Companies are increasingly integrating AI to accelerate research, optimize clinical trials, and personalize patient care. This trend underscores the growing importance of AI-driven solutions in enhancing patient treatment efficiencies and outcomes.

OM1 delivered innovative solutions to streamline research processes and improve patient outcomes. Our advanced automated prospective and retrospective research platforms have enabled our clients to conduct more efficient and robust real-world data (RWD) analyses. Combined with the breadth and depth of our specialty RWD, OM1 continues to empower leading life sciences organizations to deliver actionable insights and drive impactful decisions.

OM1 is at the forefront of this transformation – our award-winning, patented AI-powered digital phenotyping technology provides deeper patient insights and comprehensive evidence generation, resulting in a more complete understanding of the patient journey. We remain committed to empower our clients with the cutting-edge tools and insights needed for success in today’s rapidly evolving industry.

This eBook highlights OM1's top insights from 2024. We hope you enjoy it and look ahead with us to an exciting 2025!

Do you currently use AI-powered real-world data solutions to address data gaps in your patient journey analyses?

Yes, we actively use AI-powered RWD solutions
No, but we are exploring AI-powered RWD solutions
No, we rely on traditional RWD sources without AI enhancement
Unsure or not applicable

Identifying and studying hard-to-characterize patients

Identifying and studying hard-to-characterize patients to gain insights into elusive populations

POSTER

This award-winning ISPOR poster demonstrates the use of automated language processing to extract psychiatric comorbidities and SSRI-related side effects from clinical notes, to enhance real-world data analysis for depression treatment and outcomes.

Addressing Gaps in Real-World Data Sources through Automated Extraction of Psychiatric Comorbidities and Medication Side Effects from Clinical Notes

WEBINAR

This webinar explores how OM1 leverages AI and real-world data to enhance evidence generation, improve outcomes, and support regulatory and clinical decision-making in healthcare.

Polaris by OM1: Clinical Trial Recruitment for Faster, Cost-Effective Trials

WEBINAR

This webinar discusses how we used AI and RWD to identify undiagnosed cases of TRD, offering new insights and applications for mental health research and treatment development in life sciences.

Unveiling the Unseen: AI's Role in Identifying Treatment-Resistant Depression

Identifying and studying hard-to-characterize patients to gain insights into elusive populations

CASE STUDY

This case study outlines how OM1 used AI algorithms to identify treatment-resistant depression (TRD) patients in real-world data, revealing undiagnosed cases and providing insights to improve treatment strategies for complex mental health conditions.

Bringing Treatment-Resistant Depression to Light: AI-Driven Patient Discovery in Real-World Data

BLOG

This blog explains how AI is used to extract PHQ-9 depression scores from clinical notes, expanding data access for improved insights into patient outcomes in depression research.

Leveraging AI to Amplify PHQ-9 Endpoint Availability for Improving Depression Research

PODCAST

This podcast episode explores Dr. Carl Marci’s predictions for AI’s transformative role in mental health, focusing on realistic applications in areas like postpartum depression and Alzheimer’s care, while emphasizing the importance of real-world data and reducing bias to address the mental health crisis effectively.

Predictions for AI in mental health in the coming year

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Completing the patient journey with AI and real-world data

Completing the patient journey with AI and real-world data to capture the full spectrum of patient experiences and reflect the diversity seen in real-world populations

BLOG

This blog discusses how AI-driven phenotyping uncovers complex patient patterns in RWD, advancing diagnostic precision and treatment strategies in clinical research.

Enhancing Patient Journeys in Clinical Research with AI-Phenotyping

BLOG

This blog explores how AI and RWD provide a comprehensive view of patient journeys in rheumatology, enabling earlier detection, precise patient stratification, and ongoing monitoring of disease activity for chronic conditions like Lupus.

Mapping the full patient journey in rheumatology: RWD and AI in Action

WEBINAR

This webinar explains how AI-driven digital phenotyping enhances patient journey analyses by uncovering unique data patterns, enabling more precise identification, and understanding of key subgroups for improved diagnosis, treatment, and risk assessment in RWD.

Practical AI: Adding Insight to the Patient Journey with Digital Phenotyping

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Completing the patient journey with AI and real-world data to capture the full spectrum of patient experiences and reflect the diversity seen in real-world populations

WEBINAR

This webinar explores how AI and RWD are used to address complex patient journey challenges, enabling more precise patient scoring, ranking, and tagging to enhance diagnosis, treatment response, and to accelerate research and real-world healthcare impact.

Completing the patient journey: using AI and RWD to see the unseen

PODCAST

This podcast discusses how, PhenOM, OM1’s AI-powered digital phenotyping technology, leverages RWD to uncover nuanced patient insights that enhance diagnosis, treatment response, and risk prediction, advancing personalized medicine and life science research.

How AI-Powered Phenotyping Enhances the Patient Journey for Life Science Applications

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Evaluate the impact of chronic conditions with real-world data to quickly leverage the right evidence for navigating complex pathways to approval, reimbursement, and usage

POSTER

This collaborative poster between OM1 and Janssen examines adherence to esketamine nasal spray in treatment-resistant depression patients which led to greater reductions in depressive symptoms.

The Association Between Adherence to Esketamine Nasal Spray Therapy Dosing Regimen and Changes in Depressive Symptoms Among Patients With Treatment-Resistant Depression in U.S.

POSTER

This poster in collaboration with GSK dives into the findings on dupilumab’s safety and effectiveness in pediatric atopic dermatitis, helping clinicians make more informed decisions.

Disease Activity in Rheumatoid Arthritis Patients Initiating Anti-Obesity Medication in a Longitudinal US-Based Real-World Cohort

POSTER

This poster presents findings on the real-world effectiveness and safety of anti-obesity medications, utilizing advanced data analytics to assess patient outcomes and support evidence-based decision-making in obesity management.

Real-World Dupilumab Continuation in US Children and Adolescents With Atopic Dermatitis Over a 24-Month Period

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Automating prospective studies and registries

Automating prospective studies and registries to enable rapid, cost-effective, and scalable research

WEBINAR

This webinar explores the impact of automation and AI on clinical research, focusing on how these technologies streamline data collection, enhance patient identification, and improve evidence generation for more efficient and cost-effective studies.

Revolutionizing Prospective Studies and Registries with Automation and AI

BLOG

This blog explains how “velocity” is essential for maximizing the utility of RWE in healthcare to enhance data processing speed and deliver actionable insights that improve patient outcomes and support healthcare innovation.

Real-World Evidence and the Five Vs (Velocity, Volume, Variety, Veracity, and Value)