Susan Haigney

Targeted Alpha Therapy as a cancer treatment in clinical trials as a oncology therapies targeting malignant tumors with radioactive particles destroying cells | Image Credit: ©freshidea -stock.adobe.com

Radiopharmaceuticals have seen a surge in research and clinical trials as a treatment for cancer due to their ability to target specific cancer cells. Studies suggest that targeted radiation therapy may reduce the risk of side effects, according to the National Cancer Institute at the National Institutes for Health (1).

“Radiopharmaceuticals also work best when the drugs can get inside cells. But that’s not necessary for them to be effective. Once a radiopharmaceutical has stuck to a cancer cell, the radioactive compound naturally breaks down. This decay releases energy that damages the DNA of nearby cells. And when a cell’s DNA is irreparably damaged, that cell dies. Cancer cells are particularly sensitive to radiation-induced DNA damage” (1).

® spoke with Michael Ritchie, chief commercial officer at Champions Oncology, to find out what makes radiopharmaceuticals unique for the treatment of cancer.

Ritchie also talks about FDA’s draft guidance document, 

Oncology Therapeutic Radiopharmaceuticals: Dosage Optimization During Clinical Development

, which the agency published on Aug. 18, 2025 (2). The guidance was created to assist drug sponsors with identifying an optimized dosage for radiopharmaceutical therapies for oncology indications during clinical development.

PharmTech: What is unique about the use of radiopharmaceuticals to treat cancer?

 Actually, radio pharmaceuticals have been around for the past 100 years or so. They were used early on to treat more superficial tumors [such as] melanoma and using large machines to direct focused radiation to the tumors. And as that technology evolved, we were able to treat more internal tumors.

So, it’s been around for a very long time, but we’re in the middle of a transformation right now in radiopharmaceuticals, and much of that is owed to a field called antibody-drug conjugates [ADCs]. [ADCs] have been around for quite a while. That’s that magic bullet idea that you can take a chemotherapeutic or something that’s otherwise very toxic to every cell in a patient and direct that to the tumor, specifically, so that you impact only the tumor and nothing else. The first of those drugs was approved in 2000. It’s a drug called Mylotarg, and it really took us 25 years to have a good understanding of what makes a good ADC. Where can they be effective? From a therapeutic point of view, what do we need to do to make this drug long lasting in the patient?

Now we have [seen] really strong, durable responses in patients with ADCs. Now that we have a good understanding of that, we can take these radio ligands, which essentially [are] an element on the periodic table that introduces radiation in a focused way, and we can conjugate that to an antibody in the same way that these ADCs work. And so, with the advent of success in ADCs, we now have radio drug conjugates, and we’re starting to see people employ radio ligands in a similar way to a chemotherapeutic and direct it to a patient administered systemically. It’s really an exciting period, because it’s a new mechanism of action where we can potentially tackle unmet needs.

PharmTech: What are some of the specific challenges associated with the development of radiopharmaceuticals?

 There [are] real challenges across the board. There are therapeutic development challenges as well as the biology of treating these tumors. From a therapeutic development perspective, we’re still in our infancy as far as what we understand makes a good drug.

There’s so much [put] into pharmaceutical development [to make] something that can be manufactured at scale. It can sit on a shelf for a while. We can administer it to a patient, and it behaves in the way that we want. All of that chemistry, all of that biologics development, we’re just learning how to apply what we learn from ADCs into radio drug conjugates, so the chemistry of how to link this radio ligand to an antibody, [is] something that will continue to evolve, and there’s a real opportunity there to improve the therapeutic activity.

From the biology perspective, again, we’re in our infancy and understanding [of] what are the tumor types or the molecular cohorts within a tumor that are more sensitive to radio ligands. Like any chemotherapy or any therapy, certain tumors will respond. Others will not. They’ll develop resistance. And so really understanding the right cohorts of patients to treat is something that we’re still learning, and I think we’ll continue to learn as the clinical development of these programs evolves.

PharmTech: Can you please explain how clinically annotated patient-derived xenograft (PDX) models are used in radiopharmaceutical testing?

 PDXs are used from a couple different perspectives in radiopharma testing. It really comes back to that second hurdle that we need to overcome in understanding what tumor types or molecular cohorts respond. It’s really important that you do your drug testing and models that represent the tumors that your drugs [are] going to be up against in the clinic. Patients tend to be heavily pretreated. When they take an experimental medicine, their tumor has metastasized to multiple organs, and those are, unfortunately, the lesions that ultimately kill the tumor. Those are the lesions you need your drug to combat effectively. And so, using models that are representative of that biology are key. We simulate clinical trials in animals where we will take our tumor bank, we’ll grow them in animals, and then you’ll test your drug across a broad library of tumor[s] [that] simulate that clinical trial. Then, when you see where you have an effect and where you do not have an effect, we’ll look deeply at the molecular nature of these tumors and try to predict in the clinic which patients should receive the drug because they’re most likely to benefit versus those that are likely to benefit from a different type of therapy.

PharmTech: Why is it important to use real-world data in this type of testing?

 Real-world data are a real important data set, and they’ve been around for a while. And the way I think of real-world data is, is there information on patients? What’s the stage of their tumor, the metastatic nature of it? What were they treated with? How did they respond?

That’s a very important layer. But I think there’s another side to the coin that we really need to think about, and that is, what’s the molecular nature of the tumors associated with that patient? What makes those tumors tick? What are the vulnerabilities and the liabilities within those tumors that you could potentially exploit in therapeutic development? I think Champions is actually one of the unique companies that have both of those sides of the coin. We have a large data set of real-world evidence linked to very deep molecular data of the tumor, whole cell exome sequencing, RNA [sequencing], proteomics, phospholipids, cell surface proteomics. This really allows researchers to dive deep [and] understand molecular characteristics of the tumors that potentially impact survival [and] impacts resistance to the therapeutic. It just gives them real insight early on [about] how to design their clinical trials. As companies come to Champions and they simulate these clinical trials, they utilize these data for prediction purposes and for driving greater insights.

PharmTech: How does FDA’s new draft guidance on identifying dosages for clinical trials of oncology radiopharmaceuticals impact the development and approval of these treatments?

 Classical radiopharma relied on something called EBRT, or external beam radiotherapy, and that is essentially delivering a radio beam to the patient from an external source. But we’re now looking at a new wave of therapies which are injected systemically, and quite frankly, we just don’t know enough about them. And so, FDA has released new guidance that has said, ‘Hey, we want you to come to the table with a better understanding of pharmacodynamics potential liabilities from a toxicity perspective, therapeutic window. But we also want you to design your clinical trials in such a way that we can get an idea on dosimetry. We can get a good idea on toxicity from an acute perspective, but we want you to monitor these patients for a longer period of time to look for more chronic toxicities that could arise. And we want you to try different therapeutic doses, different therapeutic schedules. We really want you to throw quite a lot at this, so that if we consider approving these, we have a better understanding, or the best understanding, of what these patients are receiving’.

What are some of the challenges involved with clinical trials for radiopharmaceuticals to treat cancer?

 I think there’s both scientific and logistic challenges here. From the scientific side, we really just don’t know what we don’t know. These haven’t been around for very long, so we’re really unaware of the tumor types that respond to these types of therapies. We’re unaware of the types of toxicities.

If you think about ADCs, which are kind of a second cousin to these therapies, after more than two decades of research, we have a really good understanding of what organ types are. You can easily sustain those types of therapies, and we know how to manage the patient care for different classes. For [radiopharmaceuticals], we just, we just don’t know. And so that creates a challenge. We also really don’t understand, I think, quite yet, what makes the best possible radiotherapy from pharmaceutical sciences perspective.

From the drug development side, the logistics are very, very different. This is a highly regulated space. We’re dealing with nuclear medicine. The nucleotides themselves aren’t so readily available, so that brings challenges. And then obviously not every clinical site that will receive patients for a clinical trial is set up or equipped to offer this type of therapy, so patient enrollment can be a challenge.

And then finally, these nucleotides have a short half-life and a short shelf life. And so, it’s not like drugs can be manufactured and stuck in a refrigerator for months as they’re waiting to be used for a trial. They kind of have to be made and then used within a week, so there’s some logistical hurdles as well.

NCI Staff. Radiopharmaceuticals: Radiation Therapy Enters the Molecular Age. National Cancer Institute. 

https://www.cancer.gov/news-events/cancer-currents-blog/2020/radiopharmaceuticals-cancer-radiation-therapy

Draft Guidance for Industry, Oncology Therapeutic Radiopharmaceuticals: Dosage Optimization During Clinical Development

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/oncology-therapeutic-radiopharmaceuticals-dosage-optimization-during-clinical-development

When referring to this article, please cite it as Haigney, S. Why Radiopharmaceuticals Are Ideal for Treating Cancer. 

Articles

Radiopharmaceuticals are gaining traction in cancer treatment due to their ability to target specific cancer cells, minimizing side effects. The integration of antibody-drug conjugates (ADCs) has advanced the field, allowing for precise delivery of radiation to tumors. Challenges remain in optimizing dosage, understanding tumor sensitivity, and overcoming logistical hurdles in clinical trials. The FDA's draft guidance emphasizes the need for comprehensive understanding of pharmacodynamics and toxicity. Real-world data and patient-derived xenograft models are crucial for predicting treatment efficacy and designing effective clinical trials.

Michael Ritchie, chief commercial officer at Champions Oncology, explains what makes radiopharmaceuticals unique in the treatment of cancer.

Why Radiopharmaceuticals Are Ideal for Treating Cancer

Communication between the manufacturing plant and retail stores. | Image Credit: © Cagkan - © Cagkan - stock.adobe.com

ICE Pharma, a producer of bile acid-derived APIs, excipients, and finished dosage forms, announced on Oct. 15, 2025, that it will showcase its innovations and sustainability strategies at Booth 9.1 A94 at CPHI Frankfurt 2025, which is being held from Oct. 28–30. Highlights include the company’s ursodeoxycholic acid (UDCA) production and bile acid derivatives (1).

ICE’s products assist in the therapeutical applications for liver, metabolic, and neurological diseases and are developed in the company’s five R&D centers. The company also has a quality framework for ensuring traceability, viral inactivation, closed manufacturing systems, and regulatory compliance.

How is ICE Pharma meeting sustainability goals?

ICE Pharma will be presenting its four-pillar strategy for sustainability: Fighting Illness through Product Innovation, Caring for People, Accelerating Sustainable Operations, and Building Strong Relationships. The company is using this strategy to make decisions across resource management, waste reduction, energy sourcing, and stakeholder engagement. Following its reduce, reuse, recycle philosophy, ICE will be presenting an eco-designed booth at CPHI Frankfurt that has been built from recyclable materials from past events, minimizing environmental impact.

“At ICE Pharma, quality and environmental responsibility are inseparable,” said Agostino Barazza, Chief Executive Officer. “By mastering bile acids with rigorous controls and sustainable design, we are delivering medicines with impact and integrity.”

“Our sustainability roadmap strengthens operations and inspires confidence across our supply chain, empowering partners to deliver therapies benefiting from bile acid science,” added Roger Viney, Chief Commercial Officer.

What else is ICE Pharma showcasing at the event?

ICE will be celebrating the centennial of ABC Farmaceutici at CPHI Frankfurt, which was founded in 1925 in Turin and acquired by ICE in 2021 (2). ABC Farmaceutici will highlight its achievements and its research concentrations at the event. A special “100 Years” logo will also be unveiled at the conference.

“Reaching 100 years is not only a celebration of our past, but also a promise to the future,” said Severino Previtali, ABC Farmaceutici Business Unit director, in the press release (3). “This milestone reminds us of the generations of people who have contributed to our success, and it inspires us to continue driving innovation, building strong collaborations, and making a meaningful impact on global health.”

What is ICE Pharma’s approach to quality?

spoke with Roger Viney, chief commercial officer of ICE Pharma, aboutquality and compliance issues surrounding the use of animal-derived ingredients in the bio/pharma industry (4). In the interview, Viney talked about how regulatory harmonization is critical and increases the security of the supply chain. He also talked about the importance of traceability and knowing the origin of animal-derived material. 

ICE Pharma. ICE Pharma Highlights Sustainability and Bile Acid Expertise at CPhI Worldwide 2025. Press Release. Oct. 15, 2025.

Lavery, P. ABC Farmaceutici to Mark 100th Anniversary with CPHI Frankfurt Display. PharmTech.com. Sept. 18, 2025. 

https://www.pharmtech.com/view/abc-farmaceutici-mark-100th-anniversary-cphi-frankfurt-display

ICE Pharma. ABC Farmaceutici Celebrates 100 Years of Pharmaceutical Excellence and Innovation. Press Release. Sept. 17, 2025.

Thomas, F. DCAT Week 2025: Quality and Compliance for Animal-derived Products. PharmTech.com. March 18, 2025.

ICE Pharma, a producer of bile acid-derived APIs and excipients, will showcase its innovations and sustainability strategies at CPHI Frankfurt 2025. The company emphasizes its ursodeoxycholic acid production and bile acid derivatives for liver, metabolic, and neurological diseases. ICE Pharma's sustainability strategy includes product innovation, sustainable operations, and stakeholder engagement. The company will also celebrate the centennial of ABC Farmaceutici, acquired in 2021. ICE Pharma prioritizes quality and compliance, focusing on traceability and regulatory harmonization for animal-derived ingredients in the bio/pharma industry.

The company will also highlight its sustainability strategies and quality solutions at the event. 

ICE Pharma to Showcase Bile Acid Expertise at CPHI Frankfurt 2025

Targeted Alpha Therapy as a cancer treatment in clinical trials as a oncology therapies targeting malignant tumors with radioactive particles destroying cells | Image Credit: ©freshidea -stock.adobe.com

On Sept. 11, 2025, Medicines Discovery Catapult (MDC), a national life sciences service dedicated to drug discovery, and Crown Bioscience, a contract research organization, announced the companies were collaborating on an integrated translational biology platform for the development of radiopharmaceuticals (1). As part of the collaboration, MDC will provide knowledge in cell biology, high-resolution microscopy, radiochemistry, preclinical imaging, mass spectrometry, and multi-omic tissue analysis, and Crown Bioscience will provide discovery, preclinical, and translational platforms and services for oncology and immune-oncology products.

® spoke with Juliana Maynard, PhD, Head of Translational Imaging, at Medicines Discovery Catapult, to find out what makes radiopharmaceuticals unique and how MDC’s collaboration with Crown Bioscience can help developers of these treatments for cancer.

 What is unique about the use of radiopharmaceuticals to treat cancer?

Radiopharmaceuticals really do have enormous potential in modern medicine. They're already driving game-changing breakthroughs to patients, and we're seeing that worldwide. At their core, they are a class of medicines that contain both a radioactive form of a chemical element, something we call a radioisotope, and they can be used to both diagnose and also to treat cancers.

But what makes them so unique and so powerful is their precision; they will target radiation directly to the tumors. They work by taking a targeting molecule that binds to a specific receptor on a cancer cell and carries the radioisotope straight to the disease site. And once it's there, the gamma rays will emit either alpha or beta particles and kill the cancer cells for therapy. This means that we can both see the disease through the diagnostic tracer, and we can also treat it in a very targeted way, something we call a theranostic approach. It's highly individualized, and it's very much image-guided therapy. So instead of a one-size-fits-all [approach], what we can do is get a smarter, safer, and more patient-derived, stratified medicine approach to treatment.

Compared with traditional cancer therapies, radiopharmaceuticals spare healthy tissue. We don't get those side effects that we've seen with other cancer medicines, and because they're so precisely delivered to the cancer cells, the radiation dose to the rest of the body is significantly reduced, which lowers the risk of side effects. And we've shown proven treatment effects already in some really difficult-to-treat cancers. For example, prostate cancer and neuroendocrine tumors have shown huge traction.

Beyond the therapy, those radioactive traces and the technology advancements that we're seeing within the United Kingdom provide incredibly detailed insights to give both earlier and more accurate diagnostics. What makes them so unique is that we can combine the diagnosis and the treatment into one, and we're offering earlier detection [and] better, more precise treatment, [which] ultimately, should lead to better patient outcomes.

Challenges associated with radiopharmaceuticals

 What are some of the specific challenges associated with the development of radiopharmaceuticals?

There are some very real challenges, both in their development and delivery, that we need to overcome. Firstly, the global demand for radiopharmaceutical treatments is rising rapidly, at around 5% per year currently, and is expected to continue growing.

And here in the UK, every hospital is using them daily to help patients, but one of the biggest hurdles is access to the radioisotopes. Currently, there are no UK production routes for many of the key radionuclides that we need, which means that our clinical trials and the widespread use of these therapies are heavily dependent on imports from overseas and from reactors and cyclotrons. And naturally, that supply chain creates risks, and if those supply chains are disrupted, then the access to the treatment for the patient is immediately affected.

Secondly, there are regulatory and quality requirements. Like all medicines, radiopharmaceuticals must be manufactured, transported, and administered, and [have] very strict standards to ensure patient safety. Patient safety is at the forefront of every medicine that's produced, but because these products are radioactive and the bar for handling them, and also the compliance and how we administer them, is even higher, it can slow development and add significant complexity. And then there's also the challenge of the short half life. The radioisotopes themselves degrade very quickly. Often, the medicines have to be produced on the day that they're needed for injection, and also any delay in that transport, the production or the administration, can mean that procedures need to be canceled. This leads to a wasted product, or worse, a patient could be missing out on a timely diagnosis or treatment. While the promise of radiopharmaceuticals is huge, overcoming these challenges, particularly around reliable isotope supply regulations and logistics, is critical if we want to see the full impact for our patients, both here in the UK and also worldwide.

Assisting in the development of radiopharmaceuticals

How will the new Crown Bioscience/MDC platform accelerate the development of radiopharmaceuticals?

The partnership between Crown Bioscience and Medicines Discovery Catapult is an incredibly exciting opportunity because it creates a fully integrated pre-clinical workflow for companies that are developing radiopharmaceuticals globally. Whether they're advancing new radiotherapeutics, exploring new isotopes or optimizing their targeting agents, this partnership can encompass all of those parts of the delivery.

Within Medicines Discovery Catapult, we've built a national radiopharmaceutical platform that combines the cutting-edge imaging technologies with the world-class radiochemistry and translational expertise within the team, and Crown Bioscience bring that unrivaled strength in pre-clinical oncology models and drug discovery services.

So together, that creates a seamless pathway through from discovery into pre-clinical validation, but also into those translational imaging studies. And what this means for drug developers is that they can carry out more efficient studies, they can generate that high-quality translational data, and it will support their precision medicine strategies. The partnership really does enable that rapid and reliable testing of how a radiopharmaceutical behaves within the body and also how the body responds to it, and how effective the radiopharmaceutical itself is, all of which are absolutely critical to identifying those drug candidates and reducing that clinical development risk.

We're also leveraging our expertise across other areas within MDC, such as our cell biology, high-resolution microscopy, and multi-omic tissue analysis, enabling us to deliver robust comparator studies with approved standards of care, which in turn provides greater regulatory confidence and helps those drug developers provide and prepare stronger and successful investigational new drug submissions. By combining all of our strengths across MDC and Crown, we're not only helping innovators develop radio pharmaceuticals more efficiently, but we're giving them the tools to de-risk their assets for investment, accelerate the time it will take to get them to clinic, and ultimately improve patient outcomes. So, it's all about moving radiopharmaceuticals to market faster and doing so in a way that's smarter, safer, and more impactful for our patients.

Haigney, S. MDC and Crown Bioscience. Medicines Discovery Catapult and Crown Bioscience Form Strategic Global Alliance for Radiopharmaceutical Innovation. Press Release. Sept. 11, 2025. 

https://www.businesswire.com/news/home/20250911458780/en/Medicines-Discovery-Catapult-and-Crown-Bioscience-Form-Strategic-Global-Alliance-for-Radiopharmaceutical-Innovation

Radiopharmaceuticals offer a unique, targeted approach to cancer treatment by delivering radiation directly to tumors, minimizing damage to healthy tissue and reducing side effects. The collaboration between Medicines Discovery Catapult (MDC) and Crown Bioscience aims to accelerate the development of these therapies through an integrated translational biology platform. This partnership addresses challenges such as isotope supply, regulatory requirements, and logistical issues. By combining expertise in imaging, radiochemistry, and preclinical models, the collaboration seeks to enhance precision medicine strategies and improve patient outcomes.

Pharmaceutical Technology® spoke with Juliana Maynard, PhD, Head of Translational Imaging at Medicines Discovery Catapult, to find out what makes radiopharmaceuticals unique and how MDC’s collaboration with Crown Bioscience can help developers of these treatments for cancer.

Collaborating on the Development of Radiopharmaceuticals

Color 3d DNA molecule helix inear the lab test tube | Image Credit: © 

Bioanalysis is used in drug development to determine pharmacology, bioavailability, and bioequivalence and includes pharmacokinetic, toxicokinetic, or biomarker concentration evaluation (1). Regulators require bioanalytical methods to be validated to ensure their effectiveness (1). Advanced tools, such as artificial intelligence (AI) and machine learning (ML), are helping drug developers evaluate the complex data involved in these types of studies, especially for novel therapeutics, and generate new insights from these data.

Evolution in the field of bioanalysis techniques is often driven by the need to address analyte modalities, specifically biologic drugs, metabolites, and biomarkers, according to Steve Lowes, senior director of Scientific Affairs at IQVIA Laboratories. “Sensitivity is the typical challenge, heightened by the interest to achieve needed quantification from a smaller sample as possible,” he explains. “We, thus, have three compounding factors. One is more sensitivity. Second is a smaller sample we’re expected to work from, and third is an increasing complexity of the analyte modalities themselves.”

How are new technologies making bioanalysis more accurate, more efficient, and quicker? And what is driving, or challenging, their implementation?

While early use of AI/ML was in reports, quality control of assay validation, and study sample analysis, these technologies are being adopted more widely in bioanalysis for validated applications in development, according to Mark Arnold, owner and principal, Bioanalytical Solution Integration. “As the capabilities of the AIs have advanced, so have the applications in bioanalysis,” he says. “New applications are looking at taking GLP [good laboratory practice] or GCP [good clinical practice] protocols and bioanalytical contracts to write bioanalytical plans, perform quality control checks that integrate ELN [electronic lab notebook], instrument, and LIMS [laboratory information management system] data on a daily basis to catch errors early and identify trends that lead to failure before they happen.”

AI/ML help automate data processing and integrate complex datasets from analytical platforms, enhancing assay precision and decision-making, according to Stuart McDougall, principal research fellow, at Arcinova. “AI-driven predictive models support real-time quality control, while machine learning algorithms identify trends and anomalies to ensure regulatory compliance,” he notes. “Together, they reduce development timelines, improve operational efficiency, and support scalable, data-driven innovation across the drug development lifecycle. When integrated into systems like LIMS, these insights are directly tied to scientific context, not just numbers on a screen.”

Yasmin Emamgholi, PhD, product manager, LabVantage Solutions, adds, “Instead of spending hours combing through assay data or chromatograms, these solutions can pick up subtle trends and patterns in real time. In development, models can suggest how a compound might behave, flag outliers, or even predict interactions before they show up in the lab. On the manufacturing side, AI can spot early signals in quality control, so issues do not turn into costly failures.”

Emamgholi also points to agentic AI, which can analyze data, as well as perform tasks across the bioanalysis workflow. “For example, agentic AI solutions can help in assay development and optimization with autonomous experiment design and closed-loop optimization,” Emamgholi explains. “Such solutions can also help in manufacturing and quality control by autonomously analyzing in-process bioassay data, tracking anomalies, and helping with predictive troubleshooting, including detecting early assay or equipment issues and triggering preventative maintenance before failures occur.”

These technologies can also support predictive modeling, according to Theo de Boer, PhD, principal scientist–scientific director LCMS, at Ardena, enabling quick detection of complex biomarker patterns and enhanced pharmacokinetic and pharmacodynamic modeling.

Long Yuan, director, Department of Drug Metabolism and Pharmacokinetics, Biogen, also sees AI/ML as beneficial for data interpretation. “For example, AI can help to do the automated peak detection integration, calculate and generate the concentration data, and even integrate with the downstream report generation process,” he states, adding that AI/ML can generate study protocols and validation reports.

“Ultimately, biotech and pharma companies will be using AI to write the bioanalytical sections of filings,” Arnold assures. “Health authorities are also looking at AI as a tool to analyze data in submissions and during on-site or remote inspections of bioanalytical labs. The resulting analyses will highlight both compliance with regulations and detect problems and errors that need further review.”

Arnold cautions that controls must be put in place for AI use in regulated bioanalysis to prevent “hallucinations,” or the creation of data that have not been provided. “Not knowing if the report content is correct is not something bioanalytical labs can risk and would result in utilizing the same or greater QC [quality control] and QA [quality assurance] resources to make sure of the report’s accuracy,” he says. “Which is contrary to what AI is supposed to do: reduce human involvement and improve accuracy.” Audit trails that demonstrate how/if the data reached the correct location can help prevent this problem, Arnold suggests.

Bioanalytical workflows can be enhanced, and regulatory compliance can be supported, by incorporating large language models (LLMs) in bioanalysis, says McDougall. LLMs can automate documentation and interpret complex datasets.

“They streamline reporting by generating method summaries, validation protocols, and audit-ready records from structured and unstructured data,” McDougall says. “LLMs also assist in protocol optimization by analyzing historical assay performance and suggesting refinements. Integrated with lab systems, they enable natural language querying of experimental data, accelerating decision making. Additionally, LLMs support training and knowledge transfer by summarizing scientific literature and [standard operating procedures (SOPs)], improving consistency and reducing onboarding time. Their ability to contextualize and communicate scientific insights makes them valuable tools in modern bioanalysis.”

Yuan believes that LLMs can improve regulatory compliance for QC and QA practices by helping review ELNs and audit trails and create SOPs. “[LLMs] can be more interactive with humans. It’s more like a real human. So, [a person] can… get guidance and assistance on troubleshooting and regular bioanalytical workflows,” Yuan suggests.

“LLMs can help create a conversational digital twin by providing a natural-language interface to bio-analytical workflows, enabling scientists to converse with their assay datasets,” says Panchali Roychoudhury, senior director, TCG Digital (a part of LabVantage’s parent company, The Chatterjee Group). LabVantage analytics uses a hybrid approach to integrate semantic knowledge graphs with retrieval-augmented generation (RAG)-based GenAI models to create “a more accurate, comprehensive, contextually aware, and scalable system, with substantial reduction in hallucinations,” according to Roychoudhury. “Responses are also traceable and linked to related experiments or compounds. This combination reduces noise, expedites decision making, and strengthens confidence in the bioanalytical workflows.”

De Boer notes that “LLMs could play a role in automating data interpretation, supporting audit readiness, and improving knowledge management across projects. While their adoption in bioanalysis remains limited today, ongoing advancements suggest LLMs will increasingly help accelerate research, reduce administrative burdens, and enhance the integration of complex scientific data.”

Key to developing safe and effective drug products is the ability to perform precise quantification and structural characterization of complex molecules, according to McDougall, which can be achieved with high-resolution mass spectrometry (HRMS). He also points to the use of automated liquid handling systems and microfluidics to enhance sample processing. “These instruments are unique for their integration with digital systems, compatibility with AI-driven analytics, and ability to handle biologics and multiplexed assays—making them essential for accelerating development timelines and ensuring robust, regulatory-compliant bioanalytical data,” McDougall says.

According to Yuan, HRMS provides exceptional specificity. “For example, for oligonucleotides, sometimes the commonly used quadrupole mass spectrometer may not be able to differentiate the parent and metabolites. HRMS had a unique advantage to provide additional specificity for these types of applications,” Yuan says. He adds that HRMS can also obtain quantitative and qualitative information in the same run, allowing for data mining at a later date that can avoid sample reassessment.

Liquid chromatography (LC)–mass spectrometry (MS), automated enzyme-linked immunosorbent assay) (ELISA) (ELLA), Meso Scale Discovery (MSD), ddPCR, and flow cytometry may be used for pharmacokinetics and/or biomarker analysis, according to de Boer. Robust, reproducible results for complex modalities may be achieved by combining hybrid immunoaffinity LC–MS techniques with automated sample preparation, de Boer explains.

Although LC–MS can be more expensive and not as sensitive, Lowes sees it as a alternative to ligand binding assays (LBAs). “The benefits of mitigating the challenges and the reliance on critical reagents associated with immunoassays leads to some interesting cost and efficiency assessments of LC–MS versus LBA,” he explains. “With increasing frequency, we’re seeing LC–MS to be the best tool for the job, including in biologic bioanalysis for protein-based biologic drugs and ligand oligonucleotide therapeutics. Integral to both are also the conjugated drug structures in many oncology applications for which an antibody is directed to a tumor-associated antigen to deliver a cytotoxic payload. These are inherently complex molecules, and subsequently, so are the assays that we develop to address them. That is, we often need a free payload drug assay, a conjugated payload, and then the total antibody measurement as well.”

According to Arnold, “the improved flow cytometry instruments, with some instruments having 30 and 40 color detection ability, are being used for cellular characterization, and the improved sensitivities allow them to be applied to circulating exosome biomarkers that can detect and characterize many diseases. Mass cytometry is being used in research, and once suitable applications are identified, likely in measuring biomarkers, it will move into regulated bioanalysis.”

How do changing regulations impact bioanalysis advancements?

Development and implementation of new technologies is directly impacted by bio/pharmaceutical development and manufacturing regulations. Good manufacturing practices are often necessary to follow, and each country and/or region has its own rules. The International Council for Harmonisation (ICH) works to harmonize these regulations to help both manufacturers and regulators navigate a complex system. Bioanalysis, in particular, says McDougall, is guided by ICH M10 (2).

“Having a standard—[M10]—accepted in many major markets eliminated the need for bioanalysts to keep up with changes in each of the individual countries and adjust their practices, especially when there were conflicting expectations,” Arnold explains.

De Boer adds that “in 2025, FDA released updated guidance on bioanalytical method validation for biomarkers, emphasizing a fit-for-purpose approach that ensures sensitivity, specificity, and reproducibility (3). These evolving standards are accelerating adoption of standardized SOPs, automation, advanced assay platforms, and comprehensive documentation, enabling compliant, reproducible, and high-quality bioanalysis that supports precision medicine and faster regulatory approvals.”

FDA’s initiation of new approach methodologies to reduce animal testing in pharmaceuticals has also impacted bioanalysis (4). “The FDA announcement has certainly catalyzed ongoing efforts and support for in silico, in vitro, and ex vitro methods,” Lowes says. “The evolving developments around the organoids and organ-on-a-chip platform technologies I find particularly exciting. How bioanalysis fits into this space is still to be determined, but I suspect it will have a lasting influence on how we conduct pre-clinical stages of drug development.”

“Regulatory updates from agencies like FDA and [European Medicines Agency] demand greater precision, sensitivity, and documentation, driving innovation in instrumentation and data management,” McDougall says. “Compliance with good laboratory and clinical practices ensures data integrity and ethical standards. As expectations evolve, bioanalytical teams must adapt workflows and technologies to meet stricter requirements, ultimately improving the reliability and regulatory acceptance of drug development data.”

McDougall highlights a paper authored by members of the European Bioanalysis Forum (EBF) AI team, published in July 2025, that questions the adequacy of traditional validation frameworks for AI in bioanalysis (5). The paper “argues that static, checklist-driven validation is ill-suited for adaptive, learning systems,”
McDougall summarizes. “Instead, they propose ‘adaptive qualification,’ a dynamic, context-sensitive approach grounded in scientific oversight and continuous engagement. AI is reframed not as a tool but as a trainee, requiring lifecycle monitoring rather than one-time validation. EBF emphasizes the need for scientific stewardship, collaborative ownership across disciplines, trust built on transparency and relevance, and a shift from rigid compliance to thoughtful, fit-for-purpose oversight.”

“To be successful in delivering data accepted globally, bioanalysts must be aware of a variety of regulations and how they apply to the purpose of the analysis, type of samples they are analyzing, and the technologies,” Arnold warns. “When no regulations exist, scientists must continue to collaborate on science-based best practices.”

Bioanalytical Method Validation, Guidance for Industry

M10 Bioanalytical Method Validation and Study Sample Analysis

Bioanalytical Method Validation for Biomarkers, Guidance for Industry

FDA. FDA Announces Plan to Phase Out Animal Testing Requirement for Monoclonal Antibodies and Other Drugs. Press Release. April 10, 2025.

Timmerman, P.; et al. Why Traditional Validation May Fall Short for Artificial Intelligence in Bioanalysis: A Perspective from the European Bioanalysis Forum. 

 17(13), 835–837. DOI: 10.1080/17576180.2025.2535219

®
Vol. 49, No. 8
October 2025
Pages: 10–13

When referring to this article, please cite it as Haigney, S. Enhancing Bioanalysis and Drug Development with Advanced Tools and Technologies. 

Advancements in bioanalysis are crucial for drug development, focusing on pharmacology, bioavailability, and bioequivalence. AI and ML are increasingly used to handle complex data, improve accuracy, and streamline processes. These technologies enhance assay precision, decision-making, and regulatory compliance. LLMs further optimize workflows by automating documentation and data interpretation. New instrumentation like HRMS and LC-MS are pivotal for precise quantification and structural characterization. Regulatory changes, such as ICH M10 and FDA guidelines, drive innovation and necessitate adaptation in bioanalytical practices to ensure compliance and data integrity.

Artificial intelligence, machine learning, and novel instruments are helping drug developers evaluate complex data from bioanalytical studies.

Enhancing Bioanalysis and Drug Development with Advanced Tools and Technologies 

Advancing Radiopharmaceutical Development

On Sept. 11, 2025, Medicines Discovery Catapult (MDC), a national life sciences service dedicated to drug discovery, and Crown Bioscience, a contract research organization, announced the companies were collaborating on an integrated translational biology platform for the development of radiopharmaceuticals (1). As part of the collaboration, MDC will provide knowledge in cell biology, high-resolution microscopy, radiochemistry, preclinical imaging, mass spectrometry, and multi-omic tissue analysis, and Crown Bioscience will provide discovery, preclinical, and translations platforms and services for oncology and immune-oncology products.

® spoke with Juliana Maynard, PhD, Head of Translational Imaging, at MDC, to find out what makes radiopharmaceuticals unique and how MDC’s collaboration with Crown Bioscience can help developers of these treatments for cancer. According to Maynard, radiopharmaceuticals have enormous potential that provide game-changing breakthroughs for cancer patients, and the collaboration with Crown Bioscience will create a fully integrated pre-clinical workflow for developing radiopharmaceuticals globally as well as explore new isotopes or optimize targeting agents.

“At their core, they are a class of medicines that contain both a radioactive form of a chemical element, something we call a radioisotope, and they can be used to both diagnose and also to treat cancers,” Maynard explains. “But what makes them so unique and so powerful is their precision, and what they will do is they will target radiation directly to the tumors. How it works is taking a targeting molecule that binds to that specific receptor on a cancer cell, it will carry the radioisotope then straight to the disease site. And once it's there, the gamma rays themselves will emit either alpha or beta particles and kill the cancer cells for therapy. And what it means is that we can both see the disease through the diagnostic tracer, but we can also treat it in a very targeted way, something we call a theranostic approach. So, it's highly individualized, and it's very much image-guided therapy. So instead of a one-size-fits-all, what we can do is get smarter, safer, and more patient-derived, stratified medicine approach to treatment.”

“Compared with traditional cancer therapies, radiopharmaceuticals themselves, they spare healthy tissue,” Maynard continues. “We don't get those side effects that we've seen with other cancer medicines. And because they're so precisely delivered to those cancer cells, the radiation dose to the rest of the body is significantly reduced, which lowers those side effects. And we've shown proven treatment effects already in some really difficult-to-treat cancers, cancers.”

Click the above video to watch the entire interview.

Juliana Maynard is Head of Translational Imaging at Medicines Discovery Catapult. She has a PhD from the University of Edinburgh, and was a postdoctoral researcher at the University of Manchester.

MDC and Crown Bioscience. Medicines Discovery Catapult and Crown Bioscience Form Strategic Global Alliance for Radiopharmaceutical Innovation. Press Release. Sept. 11, 2025. 

*Editor’s Note: This transcript is a direct, unedited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.

My name is Juliana Maynard. I'm head of translational imaging at medicines discovery catapult. My background is in imaging science. I did my PhD at the University of Edinburgh, and then I moved to the University of Manchester as a postdoctoral researcher. And after that, I spent nine years in AstraZeneca before deciding to step out of industry to set up a commercial imaging service, and the aim there was to make imaging much more accessible to the wider drug discovery community. And that ambition led me to my career now in medicines discovery catapult, which is a national life sciences organization that's dedicated to turning drug discovery into meaningful commercial breakthroughs. And at MDC medicines discovery catapult, we work very closely with entrepreneur entrepreneurial scientists, and we help them validate their ideas. We derisk their investments, and ultimately, we drive productivity across the drug discovery sector and also impact to patients. And within my team, we focus on applying those translational imaging techniques, technologies like Positron Emission Tomography and computer tomography, to understand how medicines behave in real biological conditions, and this, in turn, helps accelerate drug development. It ensures that those medicines are developed to deliver the maximum therapeutic benefit to our patients. And we're also pioneering in the area of radio pharmaceutical development and translation. And here, we're combining our world class radio chemistry expertise with our state of art imaging technologies, including clinically the world's the UK's first total body PET scanner. So, alongside my role here as head of translational imaging at MDC, I'm also the director of operations and engagement for our national PET imaging platform, and this is a National Technology network that provides the UK research community with unprecedented access to total body pairs.

So, radiopharmaceuticals really do have enormous potential in modern medicine, and they're already driving game, game changing breakthroughs to patients, and we're seeing that worldwide. And at their core, they are a class of medicines that contain both a radioactive form of a chemical element, something we call a radioisotope, and they can be used to both diagnose and also to treat cancers. But what makes them so unique and so powerful is their precision, and what they will do is they will target radiation directly to the tumors. How it works is taking a targeting molecule that binds to that specific receptor on a cancer cell, it will carry the radioisotope then straight to the disease site. And once it's there, the gamma rays themselves will emit either alpha or beta particles and kill the cancer cells for therapy. And what it means is that we can both see the disease through the diagnostic tracer, but we can also treat it in a very targeted way, something we call a theranostic approach, so it's highly individualized, and it's very much image-guided therapy. So instead of a one size fits all, what we can do is get smarter, safer and more patient derived, stratified medicine approach to treatment, and compared with traditional cancer therapies, radiopharmaceuticals themselves, they spare healthy tissue. We don't get those side effects that we've seen with other cancer medicines. And because they're so precisely delivered to those cancer cells, the radiation dose to the rest of the body is significantly reduced, which lowers those side effects? And we've shown proven treatment effects already in some really difficult to treat cancers, cancers. So, for example, prostate cancer and neuro endocrine tumors have shown huge traction. And also beyond the therapy, as I say, those radioactive traces and the technology advancements that we're seeing within the UK, we can see those incredibly detailed insights to give both earlier but also more accurate diagnostics. So, you know, really, what makes them so unique is that we can combine the diagnostic, diagnosis and the treatment into one, and we're offering earlier detection, you know, better more precise treatment. And ultimately, we should. Lead to better patient outcomes.

That's a really important question, because radiopharmaceuticals themselves have enormous potential. We've seen that, but there are still some very real challenges, both in their development, but also delivery, delivery that we need to overcome. So firstly, the global demand for the radio pharmaceutical treatments themselves is rising fast, you know, around 5% per year currently and growing more and more. And here in the UK, every hospital is using them daily to help patients, but one of the biggest hurdles is the access to the radio isotopes themselves. And at the moment, there are currently no UK production routes for many of the key radionuclides that we need. And that means that our clinical trials and also the widespread use of these therapies are heavily dependent on imports from overseas and from reactors and cyclotrons. And naturally, that supply chain creates risks, and if those supply chains are disrupted, then the access to the treatment and for the patient is immediately effective. Secondly, there are regulatory and quality requirements themselves. So like all medicines ready, pharmaceuticals must be manufactured, transported and administered, and very strict standards to ensure patient safety. And patient safety is at the forefront of every medicine that's produced, but because these products are radioactive and the bar for handling them, and also the compliance and how we administer them, is even higher, and that can slow development and add significant complexity. And then there's also the challenge of the short half life. So the radio isotopes themselves, they do degrade very quickly. So often the medicines have to be produced on the day that they're needed for injection, and also any delay in that transport, the production or the administration, can mean that procedures need to be canceled. We have a wasted product, or worse, a patient could be missing out on a timely diagnostic or treatment. So while the promise of radio pharmaceuticals are huge, overcoming these challenges, particularly around that reliable isotope supply regulations and logistics is critical if we want to see the full impact for our patients, both here in the UK but also worldwide.

How will the new crown MDC platform accelerate the development of radio pharmaceuticals?

How will the new crown and MDC partnership develop? So the partnership between Crown Bioscience and Medicines Discovery Catapult it's an incredibly exciting opportunity because it creates a fully integrated pre-clinical workflow for companies that are developing radio pharmaceuticals globally, and whether they're advancing new radio therapeutics, or they're exploring new isotopes or optimizing their targeting agents. This partnership can encompass all of those parts of the delivery so here within medicines discovery catapult, we've built a national radio pharmaceutical platform that combines the cutting-edge imaging technologies with the world class radio chemistry and translational expertise within the team, but crown bioscience themselves, they bring that unrivaled strength in pre-clinical oncology models and drug discovery services. So together, that creates a seamless pathway right the way through from discovery through into pre-clinical validation, but also into those translational imaging studies. And what this means for drug developers is that they can carry out more efficient studies, they can generate that high quality translational data, and it will support their precision medicine strategies. The partnership really does enable that rapid and also reliable testing of how a radiopharmaceutical behaves within the body and also how the body responds to it and how effective the radiopharmaceutical itself is, all of which are absolutely critical to identifying those drug candidates and reducing that clinical development risk. We're also leveraging our expertise across other areas within our organization, our cell biology, high resolution microscopy and also multi omic tissue analysis, and that allows us to deliver robust comparator studies with approved standards of care, which in turn provides greater regulatory confidence and help those drug developers provide and prepare stronger and successful investigational new drug submissions. So, by combining all of our strengths, we're not only helping innovators develop radio pharmaceuticals more efficiently, we're giving them the tools to de risk their investment accelerate the time it will take to get them to clinic and ultimately improve patient outcomes. So, it's all about moving radio pharmaceuticals to market faster and. Doing so in a way that's smarter, safer and more impactful for our patients.

Videos

Pharmaceutical Technology® spoke with Juliana Maynard, PhD, Head of Translational Imaging, at Medicines Discovery Catapult, to find out what makes radiopharmaceuticals unique and how MDC’s collaboration with Crown Bioscience can help developers of these treatments for cancer.

.AI, Machine learning, Business analysis, Science and artificial intelligence technology, Cloud computing, Network, Big data, communication, Digital transformation, Innovation and futuristic. | Image Credit: ipopba -stock.adobe.com

For pharmaceutical scientists, the integration of artificial intelligence (AI) and machine learning (ML) into workflows represents a fundamental paradigm shift in how the industry discovers, develops, and manufactures medicines (1). AI is no longer a futuristic concept but a present-day reality, reshaping everything from early-stage drug discovery and clinical trial optimization to real-time process control on the factory floor (1). The synergy between groundbreaking science and innovative, AI-driven manufacturing may well define the next decade of bio/pharma, creating more personalized, effective, and accessible therapies.

How is AI accelerating discovery and streamlining development?

AI is looking to be invaluable during the early stages of drug development as it can rapidly screen vast compound libraries and predict a drug candidate's properties from just its chemical structure (2). ML algorithms can identify complex patterns in high-dimensional data, allowing scientists to de-risk projects by predicting absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties 

 before committing to resources (2, 3). This capability is particularly crucial for complex molecules with poor solubility or narrow therapeutic windows, where traditional modeling may fall short (2).

Beyond initial screening, digital tools are creating a bridge between R&D and manufacturing (3). AI-powered analysis of preclinical data can help optimize formulation conditions, while virtual models of a process or product (i.e., digital twins) offer extensive 

 testing, scenario elaboration, and process optimization (1, 3, 4, 5). These tools have the potential to save time and resources by reducing the need for physical experiments. They also have the potential to accelerate tech transfer by capturing and standardizing process knowledge, ensuring consistency from a small lab batch to a large manufacturing run (3, 5).

The impact of AI extends into manufacturing, where Industry 4.0 is driving the adoption of smart machinery, interconnected sensors, and AI-driven control systems (4). In both small-molecule and large-molecule manufacturing, the goal is to leverage data to achieve high levels of process understanding and control (4, 5). By combining AI/ML models with process analytical technology, manufacturers can monitor critical quality attributes in real time, moving toward real-time release (4, 5).

This integration enables a move from reactive to predictive—and eventually prescriptive—manufacturing (4). An AI/ML model can analyze real-time sensor data from a bioreactor, predict the final batch outcome, and drive a closed-loop optimization to adjust parameters before a deviation occurs (4,5). This can lead to improved yields, reduced variability, and more consistent product quality, when compared with standard, non-AI/ML approaches (4,5).

How can one navigate the data and regulatory landscape?

Realizing the full potential of AI hinges on high-quality, contextualized data (1,2). Process data from the factory floor is often unstructured, making it difficult for algorithms to use effectively (5). Adopting findable, accessible, interoperable, and reusable (FAIR) data principles and creating centralized data platforms are essential first steps to building a scalable, AI-ready environment (1,5). Without context, the value of data diminishes, hindering their ability to drive meaningful action (5).

Simultaneously, the regulatory landscape is rapidly evolving to keep pace with technology (6). While regulators may be open to AI-driven approaches, they emphasize the need for transparency, validation, and managing bias (2, 5, 6). The "black box" nature of some algorithms is a significant concern, pushing the industry toward hybrid models that combine the predictive power of AI with the interpretability of mechanistic models (2, 3). Establishing "good machine learning practice" will be crucial for ensuring these tools are fit-for-purpose and gaining regulatory confidence (2).

As the industry moves forward, AI will continue to augment human expertise, requiring a workforce upskilled in data analysis and robotics (1, 4). The journey ahead involves navigating these data and regulatory challenges, but the destination may be a more efficient, intelligent, and patient-centric pharmaceutical industry.

Visit PharmTech.com to watch industry experts discuss the use of AI/ML in pharma. Below is a selection of video interviews.


Susan J. Schniepp, Distinguished Fellow, Regulatory Compliance Associates, joins PDA CEO Glenn Wright and Melissa Seymour, Executive Vice President, Global Quality, Eli Lilly and Company, to talk about the regulatory and quality topics discussed at the 2025 PDA Regulatory Conference.


https://www.pharmtech.com/view/pda-regulatory-conference-2025-wrap-up

Industry Outlook 2025: Technology as a Supporting Element

® spoke with Alexander Seyf, CEO and co-founder of Autolomous, about the use of artificial intelligence and machine learning in pharmaceutical development and manufacturing.


https://www.pharmtech.com/view/industry-outlook-2025-technology-as-a-supporting-element

Drug Digest: Keeping Pace with Progressive Technologies in Biopharma Development


This episode of Drug Digest will discuss where the significant bottlenecks are in the development and manufacturing of new molecules resulting from progressive technologies, such as AI and ML, and how best to approach these challenges.


https://www.pharmtech.com/view/drug-digest-keeping-pace-with-progressive-technologies-in-biopharma-development

Quality Considerations for Using AI in Bio/Pharma


In this episode of the Ask the Expert video series, Susan J. Schniepp, distinguished fellow at Regulatory Compliance Associates, and Siegfried Schmitt, vice-president, Technical, at Parexel, discuss the quality requirements needed when incorporating AI in bio/pharmaceutical development and manufacturing.


https://www.pharmtech.com/view/quality-considerations-for-using-ai-in-bio-pharma

Thomas, F. Expanding Pharma’s Horizons Through AI and Acquisitions." 

Challener, C. A. Overcoming PK/PD Modeling Challenges. 

Haigney, S. Advancements in Biopharma Spur Innovation. 

Mirasol, F. Accelerating Adoption of Smart Tools to Advance Manufacturing." 

Markarian, J. Optimizing Data Use for Digital Transformation." 

Schmitt, S. Regulations in AI and Other Digital Technologies. 

AI and ML are transforming pharmaceutical workflows, from drug discovery to manufacturing, by enabling rapid screening of compounds, predicting drug properties, and optimizing processes. These technologies facilitate the transition from reactive to predictive manufacturing, enhancing process control and product quality. High-quality, contextualized data and evolving regulatory frameworks are crucial for maximizing AI's potential. The industry must address data challenges and regulatory concerns, such as algorithm transparency, to fully leverage AI's capabilities. Upskilling the workforce in data analysis and robotics is essential for future advancements.

This article takes a look at the developing use of AI in pharmaceutical development and manufacturing.