clinical studies Archives

Exploring the Intersection of Inflammation & Immunology Diseases

Author: Collin Labar, Life Science Partnerships, Latica

Latica’s Data Network of Gastroenterology, ENT, and Dermatology connects at the center of one high impact market: Inflammation and Immunology.

Inflammation and Immunology (I&I) is at the heart of many chronic and debilitating diseases, spanning multiple healthcare verticals. These diseases are characterized by overactive or misdirected immune responses, leading to tissue damage, impaired function, and significant patient burden.

For life sciences companies, advancing I&I research is not just about innovation—it’s about transforming patient care through cutting-edge therapies powered by data-driven insights real-world evidence (RWE). At Latica, we enable this transformation by providing the tools and insights necessary to drive meaningful change in I&I research and patient outcomes.

The I&I Landscape: A Common Thread Across Verticals

From the gastrointestinal system to the skin and respiratory pathways, inflammation plays a pivotal role in disease progression. Conditions like Inflammatory Bowel Disease (IBD), psoriasis, and nasal polyps may manifest in different organs but are united by underlying immune dysregulation. This commonality has spurred the development of therapies that target shared inflammatory pathways, such as TNF-alpha inhibitors, JAK inhibitors, and interleukin (IL) modulators.

For instance:

TNF-alpha inhibitors like infliximab (Remicade) are effective in treating Crohn’s disease, psoriasis, and even certain ENT-related autoimmune conditions
IL-4 and IL-13 inhibitors such as dupilumab (Dupixent) have emerged as game-changers foratopic dermatitis, eosinophilic esophagitis, asthma, and nasal polyps, showcasing their versatility across dermatology, GI and ENT

This cross-vertical impact underscores the importance of comprehensive research and innovation that spans beyond disease silos.

The Role of Research and Real-World Data (RWD)

To truly transform care, life sciences companies need more than clinical trial data—they need insights from the real world. RWD, typically derived from electronic health records, claims data, patient registries, and even wearable devices, offers unparalleled opportunities to address critical gaps in I&I research.

How Latica Expands the Value of RWD:

Unstructured Clinical Data Access: Latica ingests all unstructured data from siloed data sources (physician notes, procedure reports, biomarkers, biopsies, precision medicine testing) and maps them to the patient journey, providing an in-depth understanding of clinical outcomes and patient phenotypes.
Comprehensive RWD Integration: By synthesizing structured and unstructured data, we provide a holistic view of patient journeys across verticals like GI, ENT, and dermatology.
Advanced Analytics: Our cutting-edge tools uncover trends, identify treatment gaps, and support biomarker discovery, paving the way for personalized medicine in I&I.
Accelerating Drug Development: From preclinical research to post-market surveillance, Latica enables life sciences companies to design better trials, predict outcomes, and validate therapeutic efficacy in real-world settings.
Supporting Value-Based Care: With our RWD-driven insights, organizations can demonstrate treatment value, improve payer-provider collaboration, and optimize patient care pathways.

Use Cases of RWD for I&I Advancements

Refining Patient Understanding

I&I diseases often present heterogeneously, with symptoms and severity varying widely. For example, some IBD patients may experience mild inflammation managed with oral therapies, while others require biologics to control severe disease. RWD provides a comprehensive view of disease phenotypes, helping researchers segment patient populations for better-targeted therapies.

Improving Treatment Pathways

Real-world evidence helps identify how therapies perform outside the controlled environment of clinical trials. This is particularly critical in I&I, where patient adherence, comorbidities, and long-term outcomes are key factors in treatment success. By analyzing RWD, life sciences companies can evaluate comparative effectiveness and fine-tune treatment pathways to improve outcomes.

Enabling Precision Medicine

Precision medicine relies on biomarkers to tailor therapies to individual patients. In I&I, this could mean identifying patients more likely to respond to IL-23 inhibitors for psoriasis or selecting JAK inhibitors for refractory cases of ulcerative colitis. RWD accelerates biomarker discovery and validation, ensuring therapies reach the right patients faster.

Supporting Post-Market Research

Therapies in the I&I space, such as biologics and advanced small molecules, are among the most innovative yet costly treatments available. Payers and providers demand robust, real-world evidence to justify these investments. Post-market studies using RWD not only demonstrate a therapy’s value but also uncover new indications and long-term safety profiles.

The Future of I&I Research with Latica

The intersection of I&I research and RWD offers a promising path forward for life sciences companies:

Shared Pathways, Shared Solutions: Cross-vertical therapies targeting inflammation offer scalable solutions for complex diseases.
Data-Driven Innovation: RWD enables life sciences companies to identify unmet needs, improve trial design, and validate outcomes.
Patient-Centric Care: Personalized therapies informed by real-world insights empower patients and clinicians to make better decisions.

The future of Inflammation & Immunology (I&I) research lies in breaking down data silos and leveraging real-world evidence to better understand disease heterogeneity, optimize treatment pathways, and advance precision medicine. By integrating structured and unstructured clinical data across specialties like GI, dermatology, and ENT, researchers can uncover shared inflammatory pathways, improve patient segmentation, and refine therapeutic strategies. Real-world data provides the missing link between clinical trials and everyday patient care, offering insights into long-term treatment effectiveness, biomarker validation, and post-market safety. As the field continues to evolve, harnessing these insights will be essential for developing targeted, data-driven solutions that improve outcomes for patients living with chronic inflammatory diseases.

The Common Factor Between Gastroenterology, Dermatology and ENT/Allergy Diseases

Author: Dr. Robert Eisdorfer, Latica chief medical officer and co-founder

The Shared Language of Immunology

At first glance, Gastroenterology, Dermatology, and ENT/Allergy appear to have little in common. As a cornerstone of Latica’s data and analytics strategy, further explanation should be helpful.

People with seemingly unrelated diseases can have similar experiences because of one common factor: excessive type 2 inflammation, which in itself is part of a normal immune response to allergens and infections. However, when it goes into overdrive, it can contribute to inflammatory diseases such as asthma, atopic dermatitis (eczema), chronic rhinosinusitis with nasal polyps, eosinophilic esophagitis (a chronic and progressive digestive disease), or even certain environmental allergies. Treatments directed at certain interleukins (ie. IL-12, IL-23 etc)work in a variety of disease states including:

Asthma
Atopic Dermatitis (AD)
Nasal Polyps (NP), or Chronic Rhinosinusitis with Nasal Polyposis (CRSwNP)
Eosinophilic Esophagitis (EoE)
Prurigo Nodularis (PN)
Certain Food Allergies

Other types of inflammation result in diseases like IBD and psoriasis, and again treatments overlap specialty disciplines.

From a real-world data (RWD) perspective, large data sets plus predictive analytics and machine learning should enable crucial insights. The correct drug at the right time and dose for each patient, and evaluation of response and natural history in people with more than one disease (ie. eosinophilic esophagitis and asthma).

Large data sets have already provided insights into the natural history of crs with np, selection and dosing of biologics in different pt populations in IBD. Using LLM’s, images, and videos, along with longitudinal real world data will provide increased understanding of multiple inflammatory and immunologic diseases.

Explore Real-World Data With Latica

Explore how Latica’s AI-powered platform can revolutionize your approach to life science research with domain expertise in gastroenterology, otolaryngology, dermatology, and more.

Contact us today to learn about our data resources and industry-leading platform.

About the Author

Dr. Robert Eisdorfer, Chief Medical Officer and co-founder of Latica is a Gastroenterology Specialist with over 38 years of experience in the medical field. He is passionate about advancing medicine and improving patient outcomes through the application of meaningful medical research and technology. Dr. Eisdorfer works with healthcare organizations around the world to provide strategic guidance for the consideration and adoption of new technology solutions.

From a Small Startup to a Data-Rich Dream Job: My Journey as a Bioinformatics Data Scientist

Author: Yael Silberberg, VP Data Science, Latica

Overcoming the Challenges of Traditional Data

As a bioinformatics data scientist, I’ve spent years in the trenches of medical research. One of them was working at a small startup that aimed to find the best treatments for cancer based on biopsy results. In that role, the process was meticulous and slow—each study required us to carefully design a protocol, recruit patients with specific indications, and wait for months to determine whether the treatment was effective. We collected data painstakingly, one patient at a time, over long periods. This is still the case for many diagnostic startups and even large pharmaceutical companies, where every new patient adds a valuable data point, but progress is often measured in small, incremental steps.

A Paradigm Shift: The Power of Pre-Existing Data

When I moved to my new role, the first thing that blew my mind was the sheer volume and accessibility of the data. All the information we had slowly accumulated in my previous job—biopsy images, treatment plans, patient responses—was already here, waiting to be analyzed. And not just for a few patients, but for thousands, across a wide range of indications. It felt like stepping into a researcher’s dream.

While retrospective data should never fully replace the rigor of prospective data, where hypotheses are tested in real time, the ability to rapidly generate and test new hypotheses using pre-existing data is a game-changer. Instead of waiting for months or years to gather enough data to draw meaningful conclusions, I can now leverage vast datasets that span different providers, countries, indications, and populations. The potential to validate findings across multiple datasets, in a fraction of the time it would take in a traditional research setting, is nothing short of revolutionary.

The Impact on Medical Research

This transition has opened my eyes to the incredible possibilities that come with having access to such rich, diverse datasets. Here are just a few ways in which this data is transforming the research landscape:

Accelerating Hypothesis Generation and Testing: In the traditional research model, formulating and testing a hypothesis could take years. With the data now at our disposal, hypotheses can be generated and tested almost as quickly as we can code. This rapid iteration process allows us to explore a wide array of potential treatments and diagnostic markers, refining our understanding at an unprecedented pace.
Enhancing the Power of Retrospective Analysis: While prospective studies remain the gold standard, retrospective analysis using large datasets offers a powerful complement. By analyzing existing data, we can identify patterns and correlations that might not be apparent in smaller studies. Finding new biomarkers that were not even collected in traditional studies. This can inform the design of future prospective studies, making them more focused and effective.
Validating Across Diverse Populations: One of the biggest challenges in medical research is ensuring that findings are applicable across different populations and centers. With access to data from multiple providers and countries, we can validate our hypotheses in diverse patient populations. This not only increases the robustness of our findings but also ensures that treatments are more universally effective.
Streamlining Phase 4 Clinical Studies: Traditionally, Phase 4 clinical studies, which assess the long-term side effects of new drugs, are lengthy and resource-intensive. By leveraging existing data, we can conduct these studies more efficiently, monitoring patient outcomes over extended periods and identifying long-term adverse effects more quickly and without opening a new study, only by analyzing the data that is collected anyway in the clinics .

Challenges and Opportunities

Of course, there are many challenges that come with working with such vast datasets. Data quality, integration across different sources, and ensuring patient privacy are just a few of the hurdles we face. However, these challenges are far outweighed by the opportunities. Having access to this data is the dream of any researcher, offering a chance to make meaningful discoveries that can transform patient care.

The Dream of Every Researcher Reflecting on my journey from a small startup to my current role, I can’t help but feel a sense of excitement and possibility. The transition has not only expanded my access to data but has also broadened my perspective on what’s possible in medical research. The ability to work with such a rich, diverse dataset is something I could only dream of in my previous roles, and I am eager to see how this data will continue to drive innovation and improve patient outcomes in the years to come.

About the Author

In addition to her work with Latica, Yael is also the Director of Computational Biology at Point6 Bio, where she has been leading research since March 2024. With over a decade of experience in data science and bioinformatics, Yael has held senior roles at Pyxis Diagnostics, including VP of Data Science, and at BiomX Ltd, where she served as Head of Data Science. Her expertise spans big data analytics, computational biology, and bioinformatics, honed through her academic journey at Tel Aviv University, where she earned a PhD in Bioinformatics.

Explore how Latica’s AI-powered platform can revolutionize your approach to life science research. Contact us today to learn more about our data resources and industry-leading platform.