In a compelling new interview with Fierce Biotech, Isagani “Gani” Chico, vice president and global head of oncology therapeutic expertise at Fortrea, shares insights on the evolving oncology drug development landscape and the strategic role of contract research organizations (CROs).
Chico outlines four critical shifts impacting oncology research: scientific innovation, tighter economic constraints, evolving regulatory demands and growing social pressure to diversify patient representation. He highlights how new drug mechanisms and trial designs—such as basket and umbrella trials—are reshaping the path to approval.
Artificial intelligence is also transforming clinical development. Chico describes how Fortrea uses AI to analyze patient data for improved biomarker identification and trial efficiency, helping predict outcomes and streamline enrollment.
Fortrea, he notes, leverages decades of data and patient enablement tools to enhance trial flexibility. Their models—ranging from full-service to hybrid approaches—offer sponsors scalable solutions that maintain high standards while accelerating timelines.
Chico emphasizes that beyond tech and data, deep therapeutic expertise remains the cornerstone of impactful decision-making in oncology trials.
Watch the full interview to hear Chico’s perspective on what’s next in oncology R&D and how Fortrea is helping shape it.
Heath Clendenning:
Welcome everyone. And, thanks for joining. I'm Heath Clendenning with Fierce BioTech. Today, I'm speaking with Gani Chico, vice president of global head for oncology therapeutic expertise at Fortrea. Welcome, Gani.
Isagani Chico:
Thank you, Heath.
Heath Clendenning:
Let's get into it. How has the oncology drug development landscape evolved in recent years? And can you go over some biggest challenges, pharma and biotech companies?
Isagani Chico:
Over the past few years, oncology still occupies the biggest amount of resource poured into clinical development. That hasn't changed. However, the landscape has evolved very quickly, in terms of several different areas. From a scientific standpoint, the landscape has changed in a way where we have new mechanisms of action to target diseases. And also, we have combinations of different drugs with different mechanisms of action. For example, combination of chemotherapies with tyrosine kinase inhibitors, the combinations of ADCs, CAR-T therapies, and so on and so forth.
Also, the economic landscape has changed. What I mean by that is that there's still increasing pressure to complete clinical development in the shortest amount of time with the optimal amount of resources, whether it's human and financial resources. The third aspect is the regulatory landscape, which has also changed in response to the changing clinical development landscape. So it's now we find that we have to work very closely with our regulators, in terms of finding the right dose for the patients, where we have a project, Optimus, that has launched in the recent years. Also, discussions with the FDA for oncology development using complex and innovative designs, where we have in the past years you have your basket trials or your umbrella trials, and so on and so forth. Taking those drugs, using those innovative trial designs into approval.
And lastly, is the social landscape. There is a continuous rise in the global cancer burden. However, there's also increasing pressure to have the representative population of patients in the clinical trials, so that you're enrolling patients that are maybe vulnerable in terms of safety or patients that may have a different efficacy profile into your clinical trials.
Heath Clendenning:
All very good points. I have to ask, I hear about artificial intelligence probably on a weekly basis in my role. So how do AI driven insights help in identifying biomarkers and improving patient stratification in oncology studies?
Isagani Chico:
AI from a clinical development perspective, in my mind, there are two main aspects, right? One is, as you've alluded to, related to the patient, whether it's related to diagnosing the patient, or treating the patient, or monitoring the patient. In terms of diagnosis, we use AI tools in terms of looking at mutational profiles, radiologic findings, and clinical information. And using those platforms to predict whether a patient is at high-risk for certain adverse events, or actually able to respond to a particular treatment better than other patients with different kinds of profile. The second aspect of AI that we use for clinical development is in the area of making sure that we use AI in conducting or executing our clinical trials successfully, making it more efficient to make sure that we use AI tools to also help us predict patient enrollment or patient progress, and also, patient surveillance and monitoring after treatment. And lastly, as related to that, making sure that we have quality data from our clinical trials.
Heath Clendenning:
Really good applications. And as we know, for trial designs, faster is better, and we can lower some costs, that's very important. So I'm just curious, what innovative strategies is Fortrea using to enhance maybe the flexibility in oncology trial designs so we can ensure a faster and more cost-effective outcome for the sponsor?
Isagani Chico:
It's really a very relevant question, specifically because as we mentioned, the timelines are shortened, and the resources are lessened, and we still have the pressure to produce drugs that are relevant for the treatment of cancer patients. One of the tools that we use is data, whether it's external data, using our data supply partners as well as our internal data from our clinical trial experience for the past 30 years, whether it's safety, diagnostic, or efficacy data, we use all of those data sources in order to make sure that, number one, we are able to help our sponsor design clinical trials to their advantage, help find patients that may be rare, and also use that data to make sure that we can predict how the outcomes of the clinical trials will be. Also, one other aspect that's important that we do Fortrea is employee patient enablement solutions, wherein we use tools that make it easier to find patients, to enroll patients, to treat patients, and to retain the patients, and make it easier for them, as well as easier for the sites to participate in clinical trials.
Heath Clendenning:
Can you tell me about some of the key considerations for outsourcing oncology trials, versus keeping them in-house?
Isagani Chico:
In our more than 30 years experience at Fortrea, one of the main things that contribute to the decision to outsource clinical trials is really the historical precedent that the sponsors have, in terms of their experience with working with a CRO of their choice. And, when teams employ their strong teams with strong track record, good and effective communication, as well as effective quality measures. And those are the things that the sponsors consider, in terms of either repeat business or working with a CRO.
One main important aspect to consider though in that decision-making process is how the human resources complement with the CRO. What I mean by that is there are many platforms by which a sponsor can avail our CRO services, whether it's full service, meaning all functional areas to run and execute a clinical trial successfully, or just using certain functional areas, which is functional service providership relationship, where only certain functions are used in conducting the clinical trials, while the internal resources by the sponsor are used. And there's also that hybrid model. Depending on where the clinical trial is at what stage, then certain functions can come in and out based on the need at that stage of development.
Heath Clendenning:
That makes a lot of sense. So can you speak to the value of CRO therapeutic scientific expertise?
Isagani Chico:
I think that's the icing on the cake and the cherry on top of it too. Because, I think, at the end of this, right, whether we have access to a lot of data, a lot of technology, and access to AI, at the end of the day, it's still all about the patient and the decisions that we make for that patient. And then, that requires that you have a therapeutic expert helping you make those relevant decisions, whether it's on a patient level in participating in the clinical trial, or a study level in the design of the clinical trial, which populations are best for a study what safety elements are important, or efficacy elements are important, important to discuss with an expert in the field. And also, on a clinical development and a portfolio level to see how the development of a certain drug could be applicable or be relevant to the overall landscape of oncology drug development, whether it's one region of the world or globally.
Heath Clendenning:
Interesting. Gani, thank you so much for your time today.
Isagani Chico:
Thank you so much, Heath.