The Role of Biomarkers in AML Drug Discovery

The Urgency for Innovative AML Therapies

Acute Myeloid Leukemia (AML) is an aggressive blood cancer with low survival rates, despite recent progress in targeted therapies. This highlights the urgent need for innovative drug discovery approaches. Biomarker-guided strategies and robust AML models are central to advancing therapeutic development.

AML’s heterogeneity, including mutations, chromosomal abnormalities, and epigenetic shifts drives disease progression and treatment resistance. This complexity complicates universal therapies and reinforces the need for precision medicine grounded in molecular profiling.

Beyond guiding treatment selection, biomarkers in AML also play a pivotal role in monitoring disease progression and therapeutic response. Measurable residual disease (MRD) markers, for example, are increasingly used to detect subclinical disease following treatment, enabling early intervention before overt relapse. Furthermore, the integration of biomarker data into clinical trials is accelerating the development of next-generation therapies by identifying patient subgroups most likely to benefit. As our understanding of AML biomarkers deepens, so too does our ability to design more precise, adaptive, and durable treatment strategies that significantly improve patient outcomes.

Understanding AML: A Complex and Heterogeneous Disease

AML involves the rapid expansion of abnormal myeloid cells in the bone marrow and blood. Genetic mutations (e.g., FLT3, NPM1, IDH1/2, TP53), chromosomal changes, and epigenetic modifications contribute to its diversity.

The bone marrow microenvironment supports leukemic survival through stromal cells, immune components, and extracellular matrix elements that form a protective niche. Accurate models must replicate these interactions to assess drug efficacy.

AML’s clonal evolution adds another layer of complexity, as resistant subclones can emerge during treatment. Sophisticated in vivo and patient-derived systems help capture this dynamic variability.

The Power of Biomarkers in AML Therapeutics

Biomarkers play a central role in AML by enabling subtype classification, guiding therapy selection, and monitoring disease progression. Alterations such as FLT3-ITD and IDH mutations serve as both disease drivers and therapeutic targets.

Techniques like flow cytometry, PCR, and next-generation sequencing (NGS) are used to track minimal residual disease (MRD), predict resistance, and support treatment planning. Advances in multi-omics—genomics, transcriptomics, proteomics, and metabolomics—are accelerating biomarker discovery and enabling more personalized approaches.

Most Common AML Biomarkers

Several biomarkers are frequently used to classify AML subtypes, assess prognosis, and guide targeted therapies. FLT3 mutations (particularly FLT3-ITD and FLT3-TKD) are among the most common and are associated with poor prognosis. NPM1 mutations, often co-occurring with FLT3, are found in a significant subset of AML cases and are associated with favorable outcomes when FLT3 is not mutated.

IDH1 and IDH2 mutations occur in about 20% of patients and lead to production of the oncometabolite 2-hydroxyglutarate, offering a target for IDH inhibitors. TP53 mutations are less frequent but correlate with resistance to chemotherapy and poor survival. Other recurrent biomarkers include DNMT3A, TET2, RUNX1, and CEBPA, each contributing to disease characterization and therapeutic decision-making.

AML Models in Drug Discovery

AML models provide a controlled setting to study disease biology, microenvironment interactions, and treatment resistance. They are critical for evaluating drug efficacy, safety, and biomarker relevance before clinical trials.

These systems also help identify resistance mechanisms and evaluate potential combination therapies. Biomarker-integrated models enhance clinical translation by validating responses in defined molecular contexts.

In Vivo Models: A Cornerstone of AML Research

In vivo systems remain essential for testing AML therapies, particularly in replicating immune responses and bone marrow dynamics. Key models include:

• Patient-Derived Xenograft (PDX) models, which involve engrafting human AML cells into immunodeficient mice, preserving genetic features for targeted therapy evaluation. However, engraftment efficiency varies by subtype.
  
  
• Syngeneic models use mouse AML cells in immunocompetent mice, allowing for immune-oncology research but offering limited fidelity to human disease.
  
  
• Genetically engineered mouse models (GEMMs) introduce AML-relevant mutations such as FLT3 and NPM1 to study leukemogenesis and treatment resistance in vivo.
  
  
• Humanized mouse models combine human immune and leukemic cells to evaluate immunotherapies in more physiologically relevant conditions.

How Biomarkers Enhance AML Preclinical Models

Integrating biomarkers into models enables better stratification of patients, clearer prediction of outcomes, and earlier identification of resistance mechanisms. This also supports the development of companion diagnostics to match patients with suitable therapies.

Technologies Reshaping AML Modeling

Innovative tools are advancing the fidelity and utility of AML models. Single-cell sequencing captures rare subclonal populations. Patient-derived organoids offer personalized, 3D screening platforms. CRISPR editing enables precise introduction or correction of AML mutations. Advanced 3D co-culture systems recreate bone marrow niches for more accurate drug testing.

These technologies collectively enhance the predictive power and translational value of preclinical platforms.

Limitations of Current In Vivo AML Models

Despite their value, existing in vivo models have limitations. Species differences can affect drug response, and murine microenvironments may not fully replicate human marrow. Not all patient samples engraft efficiently in PDX systems, and these models are time- and resource-intensive.

Emerging solutions include refining humanized models, integrating real patient data, and incorporating advanced 3D technologies. One such innovation is Crown Bioscience’s 3D in vitro Bone Marrow Niche platform. This model mimics the human marrow microenvironment using co-cultures of stromal and hematopoietic cells embedded in biofunctional hydrogels. It allows researchers to assess drug effects on leukemic and niche cell populations, enabling high-throughput testing and mechanistic studies not feasible in traditional in vivo systems.

Integrating Models, Biomarkers & Data

Future progress in AML research depends on unifying platforms and data. Multi-omic approaches combine genomic, transcriptomic, proteomic, and metabolomic data to uncover key disease insights. AI and machine learning are being leveraged to identify biomarkers, guide therapeutic development, and optimize clinical trial design. Real-world evidence from clinical registries and patient datasets further enhances model relevance.

This integrated strategy paves the way for more effective, personalized AML treatments.

Accelerate AML Breakthroughs with Crown Bioscience

AML remains a complex and evolving challenge. But integrating advanced models, biomarkers, and data analytics is enabling more targeted, effective therapies.

Crown Bioscience offers a comprehensive suite of AML models, biomarker analysis tools, and translational platforms to bridge discovery and clinical application with confidence.