At AACR 2026, one message became clear: oncology drug development is entering a new era defined by smarter decision-making, integrated platforms, and increasingly precise therapeutic strategies. In this CrownCast episode, Crown Bioscience experts shared their perspectives from the conference, highlighting the technologies, modalities, and translational approaches that are poised to shape the future of cancer research.
From AI-enabled target discovery to spatial biology and next-generation therapeutic modalities, the discussions reflected a rapidly evolving ecosystem where innovation is no longer incremental. Instead, the industry is moving toward highly integrated workflows designed to accelerate development timelines, reduce risk, and improve patient outcomes.
Hello, and welcome to this episode of Crowncast. I'm your host, Michelle Dawn Moody. Oncology drug development is moving fast, really fast. New discoveries are changing the way researchers think about cancer biology, translational science, and the path from early research to the clinic. And at the same time, the field is becoming more complex. Biopharma teams are being asked to make smarter decisions earlier in development. They need models, data, and strategies that can better predict what will matter later on. And they need to do all of that in an environment where innovation is happening constantly. So the big question is this: which trends are truly shaping the future of oncology drug development, and which innovations are likely to have the greatest impact? And that's what we will be exploring in this episode. Crown Bioscience presented new data at the AACR annual meeting twenty twenty six, demonstrating how integrated patient derived platforms can accelerate the development of complex oncology modalities, including antibody drug conjugates, ADCs, and radiopharmaceuticals. In this episode, our subject matter experts at the event shared what stood out to them, what they see as most important, and why these developments matter right now. If you work in oncology research, drug development, or biopharma strategy, this discussion should give you a valuable view of where the field is heading and what's driving momentum across the industry. So let's get into You have one trend that everybody jump on this. But the other piece, is really exciting, is about AI, how AI is changing the live discovery landscape. And I think this will means, you know, how Kron can help our clients, both big and small, and also those AI companies, you know, to jump on that that trend and help them to leverage the latest technology. And ultimately, is try to speed up drug discovery to reduce the cost and find the right solution, right medicine, right therapies for the right patients. Last year, I think we start to focus on, we call this onshore business, right, which means the client wants to do studies locally. And that's driven by a few things. The big trend is the geopolitical dynamics. As we have seen in the past, I don't know, a few years, a few months, a few days. Right? The geopolitical landscape changes on a daily base. So how do we reduce the risks for our clients to make sure we have a stable supply chain? It was great actually to see how the organoids and other three d advanced models are picking up and how well accepted they are now. It's very nice to see actually how big of a role they play in the current developments. And other than that, I think I was very impressed with the AI sessions earlier this week. And it's very exciting to see actually what it's going to bring us in the coming There's a number of different trends that I'm really excited about AACR this year. There's precision medicine, the advances in precision medicine for patients, there's targeting early cancer, preventing cancer and also targeting resistance. But there's also a number of converging trends that I think are really exciting. So integrating AI into the workflows, the new sort of next generation targeted agents, there's radiopharmaceuticals and also the excitement around molecular glues that are targeting really hard to treat cancers like pancreatic cancer. And also the advances in technology that are being used in biomarker discovery. So there's spatial transcriptomics, there's surface proteomics and these are all converging coming together to really provide relevant models and information that can help stratify patients for the right treatments and improve outcomes for patients. Certainly, the biggest is revolution medicine, Daroxyn, Recept, I mean, in clinic, who just reported as second line pancreatic cancer result just before AACR, right? And then there's more clinical data at AACR, which is really a superstar. And then there's also Gtelc inhibitor from D3 that is also a true differentiator in second generation that is also very exciting clinical data there. So besides inhibitor itself, there's also a lot of combinatory treatments with different small molecule compound ADCs and IO therapeutics. So that also making the field very excited. And besides KRAS, I think another trend certainly is induced proximity therapeutics now become really hot, right? People moving away from first generation PROTECT, those degraders. But really, you you see the first RebTech just got a clinical proof of concept both on safety and efficacy, right? That's really exciting news. But a different, you know, smarty designed molecule now also be presented at a conference in the preclinical stage. Also very exciting. And another, you know, I see a big thing, I think, at a conference, at least from my perspective, is AI, right? I mean, it's a buzzword AI. But now AI becomes very real to impact the cancer drug R and D, you know, on smarter design of AI designed compound already entered clinic and have some proof of concept in clinic. And also, see AI certainly serve as now almost we can call a co scientist to work with drug developers to accelerate the process and also impacting the clinical management of process. It's become very real now. So that's what I say is probably the top three trends as I can say at AACR this year. But every year, there are just more ADC molecules being presented, know, generating a lot of very exciting data. But I see this year, probably the biggest trend is the payload innovation really exploded. Okay, so you see all different kinds of payloads, payload combinations, right? Last year, when you talk about dual payload ADC, people are still very skeptical about the idea, right? Although we see last year, right after AACR, the first dual payload ADC entered in clinic. But this year, when you look at ADC posters or listen to the talks, a lot of people are doing dual payloads and different kind of combinations, right? You see small molecule inhibitors, toxin drug, topo-one inhibitor, know, tubulin inhibitors, DNA damaging molecules, molecular group, all different kinds of payloads, combinations. We haven't even touched about immune stimulators, right? I mean, so there are a lot of different payload innovations. That is probably the biggest trend I see this year. Well, from talent and HR perspective, what really stands out to me is how quickly the talent landscape evolves. And I find that there's definitely a growing need for talent that has a combination of scientific expertise, strong data, and cross functional collaboration experience. Just being here yesterday and walking the floors and looking at the posters, like, ADCs are everywhere. Right? Like, that's... You see that from big pharma, and all of these CROs are sort of advertising their ADC capabilities, which makes sense. And also AI, right? Like AI is now splashed everywhere. Like, if you compare this back to, like, a few years ago at ACR, it's just... It's it's crazy how much, like, all things AI have exploded. Right? It's not even just, like, computational biologists, but it's like it's everyone. Wet lab CROs, big pharma, everybody sort of putting forth their AI capabilities. I think that a lot of a lot of things are happening right now. There's, I think, a lot of technology deferment in the current R and D and also for drug discovery. Firstly, I think from the current EACR 2026, I have learned there's maybe some changes in the three major parts. One is about AI and bioinformatics. That's a great topic in ACLR. I think AI and bioinformatics is not only a licensed tool, now it's more about discovery driving engine. I think they use it to support drug design, for new target identification, for understanding mechanism. I think that plays a bigger and bigger role for the drug discovery. And the second is about spatial biology or spatial biomarkers. That's also very important for getting popular now. Previously, there's a light to have a biomarker surface, but now it's really a decision maker surface to support new drug discovery, also identify the indications or patients for the more effective treatment. Also, the third one is about the models. I think a lot of great models we need for database for biomarker surface, not only for efficacy, for example, PDG models, also CDS models, or colour models. That's That's not only about the model, it's about biomarkers, we can support drug discovery. Also to support, to make decisions, which patient for what appropriate treatment for the clients. Now a lot of trend is about the that only focuses on advanced cancers. Also now we'll focus on some early onset cancer population. That's because a lot of young adults have more cancers currently. So this rate, this incidence is increasing. So we'll have to find some more effective treatment biomarkers to support drug development to treat those young adult cancer patients, also to have early diagnosis for the patient. It's been really interesting. This is only my second AACR and we've had a lot of questions about organoids coming in this week. I think it's been really fascinating. I know that the NAM and other things moving away from primates and moving more into preclinical and not being... And reducing the amount of animals that we use and utilize, I think is a really important trend, and organoids is certainly key to that and something that I'm sure will continue to grow. And that brings us to the end of this episode. We've covered a wide range of topics from scientific innovation and emerging research priorities to the broader trends influencing oncology drug development and, of course, business strategy. What stands out is just how quickly this field continues to evolve. The science is advancing, the tools are improving, and the expectations around translational relevance, speed, and decision making are only growing. A big thank you to our subject matter experts for sharing their insights. Their perspectives have helped unpack a complex landscape and bring greater clarity to the trends shaping oncology research today. And a big thank you to everyone who is listening. We hope this episode has given you a useful overview of the ideas, innovations, and industry shifts that matter most right now. More importantly, we hope it has offered some helpful context around how scientific progress and commercial strategy continue to intersect in oncology. Because in the end, innovation is not just about what's new, it is about what's meaningful, what improves decision making, what strengthens research, and what helps move better therapies closer to patients. If you like to hear more engaging conversations like the one you heard today, we invite you to subscribe to the podcast. Of course, you can visit crownbio.com for more information there. I'm your host Michelle Dawn Mooney. Thanks again for joining us. We hope to connect with you on another podcast soon.
Artificial intelligence was one of the dominant themes across AACR 2026, but the conversation has evolved far beyond using AI as a simple analytical tool.
Researchers increasingly view AI and bioinformatics as active discovery engines capable of accelerating target identification, optimizing drug design, and uncovering biological mechanisms that may otherwise remain hidden. This shift is transforming how biopharma teams approach oncology R&D, enabling faster and more informed decision-making earlier in development.
Crown experts noted that AI is also reshaping operational strategy across the industry. Companies are seeking talent that combines scientific expertise with data science and cross-functional collaboration skills, reflecting the growing need for teams that can bridge biology, computational analysis, and translational research.
The integration of AI into oncology workflows is especially important as therapeutic modalities become more complex. Advanced algorithms can help researchers analyze multidimensional datasets, prioritize candidates, and identify patient populations more likely to respond to treatment.
This broader movement toward data-driven development aligns with emerging industry efforts to integrate AI with translational oncology platforms and biomarker discovery workflows.
Another major takeaway from AACR 2026 was the growing acceptance and adoption of advanced preclinical models, particularly organoids and other 3D systems.
Experts emphasized how these models are no longer considered niche technologies. Instead, they are becoming central components of modern oncology development strategies because they offer more clinically relevant insights than traditional systems alone.
Integrated model platforms that combine organoids, patient-derived xenografts (PDX), CDX models, and translational biomarker analysis are helping researchers better understand tumor biology, treatment response, and resistance mechanisms. These platforms are increasingly important for complex therapeutic modalities such as antibody-drug conjugates (ADCs) and radiopharmaceuticals.
The emphasis on selecting the right preclinical model for each program continues to grow across the oncology industry. As Crown Bioscience has highlighted in previous discussions on radiopharmaceutical development, clinically relevant models can significantly improve translational confidence and reduce downstream development risk.
Importantly, AACR discussions reinforced that models alone are no longer enough. Researchers now require integrated datasets and biomarker strategies that can connect preclinical findings to patient selection and clinical outcomes.
Spatial biology and biomarker innovation also emerged as major themes throughout the conference.
According to Crown experts, biomarkers have evolved from being a “nice-to-have” capability into a core decision-making tool that informs everything from indication selection to patient stratification.
Spatial biology technologies are enabling researchers to better understand tumor architecture, immune interactions, and treatment response within the tumor microenvironment. This deeper contextual understanding is helping biopharma teams design more precise therapies and identify patients most likely to benefit.
The growing importance of biomarkers is also expanding the role of translational platforms in oncology development. Integrated biomarker testing, multiomics analysis, and advanced bioinformatics are becoming critical for generating clinically actionable insights throughout the development process.
As therapeutic strategies become increasingly personalized, these translational capabilities will play a larger role in reducing uncertainty during drug development and improving the probability of clinical success.
AACR 2026 also showcased the continued momentum behind several emerging therapeutic modalities.
KRAS inhibitors remain a highly active area of development, with particular excitement surrounding next-generation compounds and combination approaches involving small molecules, ADCs, and immuno-oncology therapies. Clinical updates presented at AACR highlighted how the field continues to evolve beyond first-generation KRAS targeting strategies.
In parallel, induced proximity therapeutics generated significant attention at the meeting. Researchers discussed how the field is advancing beyond early PROTAC approaches toward increasingly sophisticated molecular designs capable of delivering stronger efficacy and broader therapeutic applications.
Radiopharmaceuticals and ADCs also remain central areas of innovation as oncology developers pursue more targeted and precise treatment approaches. Industry-wide efforts to combine translational biology, imaging, radiochemistry, and advanced preclinical modeling are helping accelerate these programs and improve development efficiency.
Collectively, these modalities reflect a broader shift toward therapies designed to deliver greater precision while minimizing off-target toxicity.
Beyond technology and modalities, AACR 2026 highlighted an important shift in how researchers think about patient populations.
Experts pointed to growing concern around the increasing incidence of early-onset cancers among younger adults. This trend is creating greater urgency around early diagnosis, biomarker identification, and more effective stratification strategies.
The industry’s response will likely require tighter integration between translational science, diagnostics, and therapeutic development. Advanced biomarker approaches and clinically relevant models may play a critical role in identifying disease earlier and developing therapies tailored to these emerging patient populations.
At the same time, geopolitical uncertainty and supply chain considerations are influencing how companies structure their R&D operations. Several experts discussed the growing demand for localized or “onshore” studies designed to reduce operational risk and maintain stable development timelines.
These operational considerations are becoming increasingly important as oncology programs grow more globally interconnected and technically complex.
The overarching message from AACR 2026 was not simply that oncology innovation is accelerating — it is that success increasingly depends on integration.
AI, translational biology, biomarker science, advanced preclinical models, and next-generation therapeutic modalities are converging into unified development strategies designed to improve prediction, reduce risk, and accelerate clinical translation.
Organizations that can effectively connect these capabilities will be better positioned to support increasingly sophisticated oncology pipelines and deliver more precise therapies to patients faster.
As the field continues evolving, integrated translational platforms will likely become essential infrastructure for oncology innovation, enabling biopharma companies to navigate growing complexity while maintaining speed, scientific rigor, and clinical relevance.
For oncology researchers and drug developers, AACR 2026 offered a clear view of where the industry is heading — toward a future where smarter models, richer data, and integrated decision-making define the next generation of cancer therapeutics.
Crown Bioscience, (2026) Top Cancer Research Trends and Innovations Identified by Experts - Crown Bioscience. https://blog.crownbio.com/crowncast/top-cancer-research-trends-and-innovations-identified-by-experts
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