Navigating Pharmaceutical Sales with Next Best Action 2.0: A Data-Driven Approach
In the ever-evolving pharmaceutical business, the Next Best Action (NBA) approach has emerged as a crucial [...]
How AI Can Help Dermatology: Diagnosis, Treatment, Risk, and R&D
The hype around AI is finally translating into real-world value, and we are seeing broader adoption of real-world data in Dermatology. This episode of tHEORetically Speaking features Dr. Stefan Weiss, Managing Director of Dermatology and Dr. Joseph Zabinski, Managing Director of AI and Personalized Medicine at OM1, who discuss the path to personalized medicine and AI-powered clinical decision support in dermatology.
Transformative Role of Artificial Intelligence in Healthcare: Enhancing Patient Care, Clinical Research, Supply Chain Resiliency and Workforce Optimization
Artificial intelligence (AI) is transforming the healthcare industry in impactful ways. AI enables higher-quality patient care [...]
Global Planning to Local Execution Market Success
Moving beyond static evidence development to ensure local market access success; responding to recent changes in governmental drug regulations [...]
Trends Projected to Reshape the Healthcare Landscape in 2024
Several societal drivers will shape the healthcare landscape in 2024, including a longer-living population, transformative technologies, and global economic uncertainty. [...]
Between Two Scientists: Data Linkage – Like Making a Fine, Blended Wine from Varietal Data Sources
This episode of tHEORetically Speaking features host Meg Richards, Executive Director of Solutions at Panalgo, who speaks with Erik Maul, Senior Director of Data Partnerships at Panalgo about data linkage.
Swoop Launches AI Tool for Medication Adherence Predictive Targeting
Swoop, a prominent provider of custom audiences for the pharmaceutical and life sciences industry, has launched [...]
Global Data Breach Costs Rise to Record High
IBM's 2023 Cost of a Data Breach Report shows that the average global cost of a data breach has reached [...]
Peterson Center on Healthcare Launches Institute to Evaluate Digital Health Technologies
The Peterson Center on Healthcare has launched the Peterson Health Technology Institute (PHTI). The PHTI is a nonprofit organization dedicated [...]
Is AI the Future of Pharma?
Here's What People Are Saying... ChatGPT is revolutionizing the pharmaceutical industry. Artificial intelligence and machine learning are expediting medication development, [...]
Transforming clinical research: Scaling real-world data across diseases with expert-led AI
The promise of improving patient care and outcomes through RWD has been understood for some time, but overcoming the fragmentation and inaccessibility of disparate data sources across disease states has proven to be a hard challenge across the industry. We’re not learning fast enough— this is where clinical expert-led AI can help. By using AI to standardize unprecedented volumes of data, uncover clinical details that have previously been hidden in free text notes, and represent full patient journeys in near real-time, researchers can ask and answer complex questions for targeted populations like never before.
Synthesise RWE and AI. Transform patient-driven healthcare
As the volume of the real word evidence data increases, the mechanisms to collect and translate the data into meaningful insights for pharmaceutical organisations becomes increasingly complex. Advances in technologies such as artificial technology have delivered global excitement, but mastering how to leverage AI for meaningful patient outcomes remains uncracked.
AI Miracles Won’t Transform Healthcare … But Another Miracle Will
Barely a day goes by without a headline touting how some new generative AI system will transform our lives [...]
Clinical Trial Innovation: How Healthcare Technology is Evolving
Join us as we discuss how the healthcare landscape is changing in technology and clinical trial innovation, including diversity improvement, leveraging real-world evidence, comparative arms, and decentralized clinical trials.
How to assess the quality of AI output when structuring unstructured medical data
Looking to empower your organizations with high quality patient data? Human abstraction has long been considered the gold standard for extracting high quality information from EHR data. With the rise of NLP, large language models, and machine learning, the question becomes: how should we evaluate these new technologies against the traditional abstraction methods?
Improving Patient Outcomes: AI-Based Phenotyping for Diagnosis, Treatment, and Clinical Trials
Join a panel of OM1’s clinical experts in cardiometabolic disease, immunology, and mental health as they explore how Artificial Intelligence (AI) can find phenotypic patterns and unlock insights hidden in real-world data.
Hard to Define, Harder to Find Patients: Using AI & Real-World Data to Understand Treatment Resistant Depression
Mental health conditions can take a staggering toll on an individual physically, socially and financially. Many patients languish with [...]
Will 2023 Be the Year AI Disrupts Healthcare?
Before we get to 2023, let’s talk about 2022—specifically about a technology that DIDN’T fulfill its promise last year: [...]
Digital therapeutics: Software is now entering mainstream therapeutic care
The news that a prominent insurer had decided to cover a digital therapeutic for opioid disorder spurred national headlines recently. In this case, the therapeutic had a breakthrough designation from the FDA. That payer decision underscored the potential as well as the challenges that have arisen around developing and marketing digital therapeutics, which have become a fast-growing segment within digital healthcare. DTx delivers clinical interventions directly to patients via software to treat, manage or prevent disease - ranging from behavioral health conditions to diabetes. We'll take a close look at this burgeoning field and see where we're headed in the years to come.
Utilizing RWD, Machine Learning, and Systems Biology
Industry leaders answer questions on utilizing real-world data, machine learning, and systems biology for benefiting therapeutic development.
Social Media Data: Opportunities and Insights for Clinical Research
Hear four experts from ICON and Kap Code provide insights on how to collect, use, analyze, and interpret social media data in different contexts. These experts share knowledge from over fifteen years of successfully developing and adapting algorithms to treat this kind of data.
Cutting Edge Conversations: Addressing Orphan and Rare Diseases
Joseph Zabinski, PhD, MEM, and Jonathan Kish, PhD, MPH, discuss how research groups are working in the realm of orphan and rare diseases.
The Value of a Multi-Source Real-World Data Strategy: How to Overcome Gaps and Limitations
Syapse experts share how to establish high quality, real-world datasets by using a multi-source strategy. A single source of data is often not enough to generate meaningful real-world evidence.
A Magnet for the Haystack: Using AI to Find Rare Disease Patients
Correctly identifying a patient with a rare disease can be like looking for a needle in a haystack: by definition, each rare disease has fewer than 200,000 patients out of more than 300M people in the US.
Using AI, NLP and Data Visualization with RWE to Generate Insights into Care Gaps: Retrospective Cohort Analysis of Fracture Risk in Patients with Osteopenia and Osteoporosis
This blog reports practical uses of RWD sourced from the largest, cloud-based electronic health record (EHR) platform in the United States, offered by Veradigm® as part of its Health Insights database.
