Precision Medicine in IMIDs - The Path to Improved Healthcare Outcomes
July 14, 2025
Justyna Lisowska
In the last few years, precision medicine — an approach that tailors medical treatment to the individual characteristics of each patient — has been successfully applied to the field of oncology, providing more targeted, effective therapeutics for previously uncurable medical conditions. This paradigm shift has firmly established precision therapies in clinical practice within oncology-related fields, such as immuno-oncology. However, while oncology has seen substantial benefits, other therapeutic areas, including immune-mediated inflammatory diseases (IMIDs), are only beginning to explore the potential of this transformative approach. Applying precision medicine to IMIDs holds promise for improving treatment specificity, efficacy, and patient outcomes.
How Does Precision Medicine Work in IMIDs?
Immune-mediated inflammatory diseases (IMIDs) consist of more than 100 (1) clinically unrelated, pathological conditions characterized by chronic, organ-targeted, or systemic inflammation resulting from the aberrant response of the human immune system to either external infectious factors, tissue micro-damage (auto-inflammatory disorders) or native antigens (autoimmune diseases). While the exact pathogenic mechanisms underlying such conditions — including rheumatoid arthritis (RA), inflammatory bowel disease (IBD), psoriasis, systemic lupus erythematosus (SLE), asthma, multiple sclerosis (MS), or type 1 diabetes — remain to be elucidated, it is generally accepted that they share common molecular pathways triggered by a complex interplay between genetic and environmental factors. Indeed, genome-wide association studies (GWAS) have recently identified a wide array of immune-related genes associated with IMIDs revealing numerous loci shared between multiple inflammatory conditions (2-3).
Among environmental factors, lifestyle factors such as smoking, physical activity, stress, and diet — as well as microbial exposure, hormones, medications (e.g., antibiotics or NSAIDs), or pollutants — have been shown to increase the susceptibility to certain IMIDs and be responsible for their rising incidence in an industrialized world (4-9). Associated with fatigue, substantial pain, progressive organ or systemic failure, and concomitant depression and anxiety (10-11), IMIDs reduce patients’ quality of life (QoL) and can lead to their premature death. IMID patients also commonly develop multiple inflammatory disorders over time, which further exacerbates their physical condition and vitality —significantly impairing work-related productivity. High healthcare costs associated with long-term treatment (For IBD alone in Europe, €4.6–5.6 billion per year (12)) and other indirect costs (such as disability payments or early retirement) impose a substantial financial burden on the entire economy.
To address these challenges, precision medicine offers a promising alternative to the traditional "one-size-fits-all" approach. By identifying individual differences at the molecular level, precision medicine enables the development of more targeted and effective therapies. This involves the integration of multiple layers of biological information — commonly referred to as multi-omics — including genomics, epigenomics, metabolomics, and microbiome data. Rather than focusing on a single data type, this holistic approach allows for a more comprehensive understanding of disease mechanisms and patient-specific therapeutic responses, paving the way for more personalized and impactful treatment strategies in IMIDs.
Challenges in Precision Medicine in IMIDs
As different IMID conditions affect different body parts (joints, muscles, skin, digestive, respiratory and nervous system as well as other internal organs), despite having systemic consequences, they are often considered as organ-specific and thus, are diagnosed and treated by different specialists (e.g., rheumatologists, dermatologists, gastroenterologists or neurologists). Clinical diagnosis relies on the qualitative assessment of the affected organ(s) and collection of symptoms (tiredness, pain, depression) subjectively reported by patients and evaluated by organ/symptom-specific scores or metrics. However, since IMID symptoms vary widely across and within a particular disease, and perception of their severity may be different between patients, this approach does not reflect the full picture of the disease and cannot result in an accurate diagnosis and efficient treatment. Composite scores used for RA (DAS28), or Psoriasis (PASI), including biomarkers, lab test results, fatigue, and pain scores provide a more complete description of the burden of the disease but do not describe the underlying pathological mechanism which would enable the provision of effective medical treatment.
IMID Treatment and the Promise of Biologics
As different IMID conditions affect various parts of the body — including joints, muscles, skin, the digestive, respiratory, and nervous systems, as well as other internal organs — they are often considered organ-specific, despite having systemic consequences. As a result, they are typically diagnosed and treated by different specialists (e.g., rheumatologists, dermatologists, gastroenterologists, or neurologists). Clinical diagnosis relies on the qualitative assessment of the affected organ(s) and the collection of symptoms (e.g., tiredness, pain, depression) subjectively reported by patients and evaluated using organ- or symptom-specific scores or metrics. However, since IMID symptoms vary widely across and within individual diseases — and patients may perceive symptom severity differently — this approach does not capture the full complexity of the disease and often fails to support accurate diagnosis and effective treatment(13).
Composite scores used in clinical practice, such as DAS28 for rheumatoid arthritis or PASI for psoriasis, incorporate biomarkers, lab test results, fatigue, and pain scores to provide a more comprehensive view of disease burden. However, these metrics still fall short of describing the underlying pathological mechanisms that would enable truly effective and personalized medical interventions.
Over the past few decades, the introduction of biologics and small molecule drugs has significantly improved outcomes for IMID patients (14). These therapies target key pro-inflammatory cytokines — including TNF-α, interleukins 1, 6, 17, 23, 18, and 15 — that drive chronic inflammation. Since their emergence in the 1990s, biologics have revolutionized IMID treatment by offering more targeted and durable responses compared to conventional immunosuppressants. Despite these advances, many patients still experience suboptimal responses or adverse effects, highlighting the need for more precise, mechanism-based treatment strategies (15).
AI and Machine Learning Guiding Personalized IMID Care
Artificial intelligence (AI) and machine learning (ML) are playing an increasingly important role in advancing personalized care for immune-mediated inflammatory diseases (IMIDs). By analyzing complex, multi-layered datasets — including clinical, imaging, and molecular data — these technologies help identify patterns that support earlier diagnosis and more precise treatment decisions.
For example, radiomics-based ML models can detect subtle inflammatory changes in imaging data, while integrative platforms like ImmunoNet combine genetic and clinical information to improve patient stratification and therapy selection. These tools move beyond symptom-based assessments, enabling a more mechanism-driven approach to care. As AI continues to evolve, its integration into clinical workflows promises to make IMID treatment more predictive, personalized, and effective.
Downfalls of Current Treatment
Despite their clinical success, biologic therapies are not universally effective. A significant proportion of patients either fail to respond or relapse after an initial period of improvement. Moreover, many biologics are associated with serious side effects, including an increased risk of opportunistic infections, malignancies, cardiovascular complications, and demyelinating diseases — largely due to their immunosuppressive effects (16 - 19). Additional concerns include off-target effects, immunogenicity, and the substantial economic burden of treatment. For instance, a 2016 retrospective study reported that anti-TNF biologics in the U.S. cost between $24,000 and $26,000 per patient annually (20).
The declining efficacy of biologics over time may reflect the evolving nature of IMIDs. As diseases progress, different molecular pathways may become dominant. For example, in systemic sclerosis (SSc), IL-6 plays a key role in early inflammation, but IL-13 becomes more prominent during later fibrotic stages—reducing the effectiveness of IL-6-targeting therapies like tocilizumab (21). This shift underscores the dynamic and heterogeneous nature of IMIDs.
The Need for a Precision Medicine Approach
The examples above highlight that while IMIDs may share common inflammatory pathways, distinct mechanistic patterns within phenotypically similar conditions can significantly influence treatment response. This variability underscores the need for a precision medicine approach — one that moves beyond generalized treatment and targets disease at the level of individual endotypes.
To realize this vision, the integration of prognostic and predictive biomarkers, along with insights from genomics, epigenomics, metabolomics, microbiome, and exposome data, is essential. Such multi-omics approaches, combined with AI-driven analytics, can support the design of innovative clinical trials, such as master protocols (umbrella and basket trials), which have shown success in oncology but remain underutilized in IMID research.
By adopting a multi-biomarker strategy, clinicians can better diagnose, stratify, and match patients with therapies tailored to their specific disease mechanisms. Mapping disease endotypes to drug endotypes — the molecular effects of a therapeutic agent — can lead to more effective, less toxic treatments (22-23). This concept, already proven in oncology (24), should now be extended to IMIDs (read more).
However, unlocking the full potential of precision medicine requires robust IT infrastructure, scalable computational tools, and secure data-sharing frameworks. Collaboration across academia, industry, and regulatory bodies will be key to accelerating this transition. With continued investment in research, data integration, and AI, precision medicine has the potential to transform IMID care — delivering more personalized, effective therapies and significantly improving patient outcomes.
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