Radiopharmaceutical development is accelerating. Preclinical strategy must evolve with it.

Radiopharmaceuticals are rapidly becoming one of the most dynamic areas of oncology drug development. By combining molecular targeting with controlled radiation delivery, these therapies introduce a powerful new dimension to precision medicine, enabling both targeted treatment and quantitative imaging.

The clinical success of targeted radioligand therapies such as Lutathera for neuroendocrine tumours and Pluvicto for metastatic prostate cancer has demonstrated that radiopharmaceuticals can produce durable responses in patients with limited therapeutic options. These milestones have helped move radiopharmaceuticals from a specialised therapeutic niche towards a central role in modern oncology pipelines.

As a result, investment in the field has accelerated rapidly. Large pharmaceutical companies, venture-backed biotechnology firms, and academic research groups are expanding radiopharmaceutical programmes, exploring new isotopes, targeting ligands, and therapeutic strategies.

In a previous article, I discussed how regulatory expectations are evolving alongside this scientific progress. The FDA’s draft guidance on dosage optimisation emphasises the importance of integrating discovery, preclinical research, and clinical development within a continuous translational framework supported by robust data.

What is becoming increasingly clear, however, is that regulatory evolution is only part of the story. As radiopharmaceutical innovation accelerates, the scientific infrastructure used to evaluate these therapies has not always kept pace with the complexity of the field.

In many development programmes today, the limiting factor is no longer isotope chemistry or targeting ligand design. Instead, it is the ability to generate preclinical evidence that reliably predicts how radiopharmaceuticals will behave in patients.

The emerging translational bottleneck in radiopharmaceutical R&D

Radiopharmaceuticals differ fundamentally from conventional oncology drugs because they sit at the intersection of two scientific disciplines: tumour biology and radiation physics. Their therapeutic activity depends not only on molecular targeting, but also on the physical characteristics of the radionuclide itself.

Half-life, emission type, radiation energy, and tissue penetration all influence therapeutic effects. These properties interact with tumour biology in ways that are often difficult to predict using traditional preclinical systems.

As a result, evaluating radiopharmaceuticals requires a multidimensional understanding of tumour targeting, biodistribution, radiation dosimetry, and biological response.

Historically, many oncology programmes relied on simplified preclinical models to generate early efficacy data. While these models remain useful for initial screening, they often lack the biological complexity necessary to evaluate radiopharmaceutical behaviour accurately.

Cell line xenograft models, for example, frequently exhibit homogeneous receptor expression and simplified tumour architecture. In contrast, patient tumours display significant heterogeneity in receptor density, vascularisation, and microenvironmental characteristics, all of which can influence radioligand uptake and retention.

Similarly, basic biodistribution studies may provide general pharmacokinetic insights, but rarely capture the spatial distribution of radiation exposure within tumours and surrounding tissues.

As radiopharmaceutical development accelerates, these limitations are becoming more apparent. Sponsors, investors, and regulators increasingly expect stronger translational evidence earlier in development to reduce risk and support clinical strategy.

Why tumour biology matters more for radiopharmaceuticals

The effectiveness of a radiopharmaceutical depends on achieving a delicate balance between tumour targeting and radiation exposure to healthy organs.

This balance is influenced by several biological factors, including receptor density, tumour vascularisation, internalisation kinetics, and intratumoural heterogeneity. These characteristics determine how much radioligand accumulates in tumours relative to healthy tissues.

For therapies using beta-emitting isotopes, crossfire radiation can partially compensate for heterogeneous uptake. In contrast, alpha-emitting isotopes deliver extremely potent radiation over very short distances, making tumour architecture and cellular distribution particularly important.

These dynamics mean that minor differences in tumour biology can have significant effects on therapeutic index.

Preclinical systems that fail to capture clinically relevant tumour characteristics may therefore produce misleading results. An agent that performs well in simplified models may behave very differently when confronted with the biological complexity of human disease.

Building more predictive preclinical models

To address this challenge, many radiopharmaceutical developers are increasingly turning to tumour models that preserve key features of human cancer biology.

Patient-derived xenograft (PDX) models provide one such platform. Generated directly from patient tumour tissue, these models maintain histological structure, molecular characteristics, and tumour heterogeneity that more closely resemble the original disease.

For radiopharmaceutical research, this biological realism enables more meaningful evaluation of radioligand uptake, tumour retention, and tumour-to-organ radiation ratios.

Studying compounds across panels of PDX tumours also allows researchers to explore variability in target expression and treatment response across clinically relevant tumour populations. These insights help developers understand where therapies are most likely to succeed and where additional optimisation may be required.

Importantly, PDX models often originate from patients who have received multiple prior therapies, reflecting the biology of tumours encountered in clinical trials.

As a result, they can provide valuable insights into how radiopharmaceuticals perform in treatment-resistant disease settings.

Integrating imaging and dosimetry into preclinical research

Radiopharmaceutical development also relies heavily on imaging technologies to characterise how radioligands distribute throughout the body. In preclinical research, traditional biodistribution studies using tissue sampling and cut-and-count analysis remain the gold standard for measuring radionuclide uptake across organs and tumours. However, imaging technologies increasingly complement these methods by enabling non-invasive visualisation of radiotracer behaviour in living systems.

Nuclear imaging techniques such as PET and SPECT provide valuable insights into tumour uptake, clearance kinetics, and organ exposure. PET imaging is generally regarded as the most quantitatively accurate modality, enabling highly sensitive measurement of tracer distribution and dynamic pharmacokinetics. SPECT imaging, meanwhile, offers broad isotope compatibility and is widely used to study therapeutic radionuclides that cannot be evaluated using PET.

One of the most important advantages of nuclear imaging in preclinical studies is the ability to perform longitudinal measurements in the same subject over time. Unlike traditional biodistribution studies, which require animals to be sacrificed at each time point, imaging allows researchers to repeatedly observe tumour targeting and radioligand retention within the same animal. This capability reduces inter-animal variability and provides a clearer picture of how radiopharmaceuticals behave across the full course of an experiment.

When combined with biologically relevant tumour models, imaging becomes a powerful translational tool. Researchers can observe how tumour characteristics influence radioligand uptake and retention while generating datasets that support dosimetry modelling and early clinical planning.

Connecting molecular data with therapeutic response

Advances in molecular profiling are further enhancing the translational potential of radiopharmaceutical development.

Genomic, transcriptomic, and proteomic analyses of tumour models can reveal how biological pathways influence radioligand binding and radiation sensitivity. When combined with imaging and efficacy data, these insights help identify biomarkers associated with treatment response.

Such approaches support the broader shift toward precision radiopharmaceutical development. Rather than treating these therapies as fixed-dose interventions, researchers are increasingly exploring how tumour biology and molecular subtype influence treatment outcomes.

Integrating molecular data with imaging and dosimetry creates a more comprehensive picture of therapeutic activity, aligning with the FDA’s emphasis on evidence-driven dose optimisation and personalised treatment strategies.

How translational data informs radiopharmaceutical development

In practice, radiopharmaceutical development programmes increasingly rely on integrated translational datasets to guide early decision-making. Before initiating in vivo studies, research teams often evaluate available tumour models to identify systems that reflect the biological characteristics of the intended clinical population.

This process typically begins with the analysis of tumour datasets that include molecular expression profiles, treatment history, and other biological features relevant to the target of interest. By reviewing this data, researchers can select tumour models that capture meaningful variation in receptor expression or disease biology.

For example, a developer pursuing a radioligand targeting a specific cell-surface receptor may evaluate tumour models representing a range of expression levels. Studying compounds across this spectrum allows teams to assess how receptor density influences radioligand uptake, tumour retention, and therapeutic response.

Once suitable models are selected, imaging and biodistribution studies can be used to evaluate tumour targeting and tissue distribution under different experimental conditions. These experiments help inform decisions about isotope selection, ligand design, and dosing strategy.

Equally important, translational studies often involve close collaboration between radiochemists, imaging specialists, and tumour biology experts. These multidisciplinary discussions help ensure that experimental design reflects both the biological behaviour of the tumour models and the physical properties of the radionuclide being evaluated.

By integrating tumour biology, imaging data, and radiochemistry considerations early in development, researchers can build a stronger scientific rationale for advancing radiopharmaceutical candidates into clinical testing.

Translational strategy in radiopharmaceutical development

As radiopharmaceutical pipelines expand, many development teams are also recognising that successful programmes depend not only on experimental data, but on the strategic integration of that data into clinical development planning.

Radiopharmaceuticals introduce unique challenges in this regard. Decisions related to isotope selection, administered activity, dosing schedule, and imaging strategy are often interconnected. The physical properties of the radionuclide must align with the biological behaviour of the targeting ligand and the characteristics of the tumour models used in preclinical studies.

For this reason, radiopharmaceutical development increasingly involves close collaboration between radiochemists, imaging scientists, tumour biologists, and translational researchers. These multidisciplinary discussions help ensure that early experiments generate data that can inform downstream regulatory and clinical decisions.

For example, preclinical studies may be designed not only to demonstrate tumour targeting, but also to evaluate tumour-to-organ radiation ratios, retention kinetics, and dose-response relationships that could influence first-in-human study design. Imaging and biodistribution data can then be incorporated into translational modelling frameworks that support dose selection and safety assessment.

By approaching preclinical research with clinical translation in mind, development teams can reduce uncertainty as programmes move towards IND-enabling studies and early-phase trials. This integrated strategy is becoming increasingly important as regulatory agencies emphasise data-driven dose optimisation and stronger translational justification across the drug development continuum.

The future of radiopharmaceutical development

Radiopharmaceuticals are redefining how oncology therapies are designed and delivered. By combining molecular targeting with controlled radiation exposure, these therapies offer powerful opportunities to treat cancers that have historically been difficult to address.

At the same time, their unique biology and physics demand more sophisticated approaches to preclinical research. As the field continues to expand, developers must increasingly integrate biologically relevant tumour models, quantitative imaging, and molecular profiling into cohesive translational research strategies.

Programmes that adopt this integrated approach early in development will be better positioned to generate the evidence required to support dose optimisation, guide patient selection, and reduce uncertainty as candidates move toward IND-enabling studies and clinical trials.

Radiopharmaceutical innovation is advancing rapidly, but the success of future therapies will depend not only on new isotopes or targeting ligands. It will depend on the strength of the translational science that connects discovery to clinical development. By building stronger links between tumour biology, imaging, and dosimetry, researchers can create development strategies that accelerate progress while improving confidence in clinical outcomes.

About the author

Denis R. Beckford-Vera, PhD, is head of radiopharmacology at Champions Oncology. A radiopharmaceutical R&D leader with 20+ years of experience advancing novel imaging agents and targeted radiotherapies from discovery to clinic, he specialises in immunoPET and alpha/beta-emitting therapeutics, with recognised achievements in CD46- and CD33-directed radioimmunotherapies. Beckford-Vera has built and led high-performing teams, established laboratories, and guided programmes through IND-enabling studies and first-in-human trials. He holds a PhD in Nuclear Chemistry, a miniMBA from Rutgers, and executive training from Wharton. He is the author of more than 25 peer-reviewed publications, four book chapters, and two US patents, blending deep scientific expertise with strategic leadership in precision oncology.