From new product launches to patient journeys and communications testing, pharma insights teams are being asked to deliver more precise answers, more frequently, and in less time. In our recent conversational masterclass, experts from Novartis and Reach3 explored how modern research approaches can help meet that challenge.
Amr Eltokhy, Senior Business Manager at Novartis, joined Matt Kleinschmit, our CEO and Founder at Reach3, and Amr Salouha, who leads our pharma practice, to discuss the forces reshaping pharma research and how conversational approaches can help teams respond.
A full recording is available here. Here are some of the key takeaways from their presentation.
Pharma research needs are changing
Eltokhy highlighted three changes shaping what pharma teams need from research: patient empowerment, digital and AI transformation, and rapid advancement within the industry.
Patients and caregivers are becoming more active in treatment discussions, while enthusiasm around AI continues to grow. But Eltokhy emphasized the importance of focusing on its practical value.
“Does it help in understanding something better? Does it help us make a more informed decision, or does it at least help us reduce the cost?”
— Amr Eltokhy, Novartis
Add evolving treatment options, changing competition and shifting research questions, and the pressure becomes clear.
“We need to know more. We need the answers to be more precise. We need them faster. And we need them more frequently.”
— Amr Eltokhy, Novartis
That tension, more depth, less time, became a thread throughout the session.
Why conversational research fits the moment 
Matt described what Reach3 calls the “third wave” of research: leveraging mobile chat technology, AI, and conversational research design to engage people through the devices they already use every day.
The webinar explored how these techniques can be applied to three common pharma research challenges.
Go beyond the numbers in ATU (Awareness, Trial & Usage) and launch tracking
New product launches make the need for speed and precision particularly clear. Timelines can shift, competitors continue moving, and the market begins reacting once a new treatment is introduced.
One case study demonstrated a different approach through a pre-launch pulse program among dermatologists and allergists. Across eight rapid quant and qual pulses, approximately 500 patient records were collected, and more than 100 Healthcare practitioner's selfie videos were uploaded, providing a view of changing perceptions, evidence requirements and anticipated early adoption behavior. (Learn more here)
Use AI to ask the next question
AI-supported probing offers another way to add depth. Eltokhy described the frustration of seeing broad responses such as “efficacy” or “safety” and wanting to understand exactly what drove a physician’s decision.
“I have often been reading a research report, and I have a thought, like, I wish I could ask the physician just one more question.”
In a multiple sclerosis study, the study asked 30 physicians to review a realistic patient profile and select a treatment follow-up question that responded to what each physician had already said, rather than relying solely on a fixed list of probes.
“For me, the value was being able to ask the next question while the conversation was still happening.”
— Amr Eltokhy, Novartis
This helped uncover treatment priorities, trade-offs and reservations while maintaining the scale and speed of quantitative research.
Connect the patient journey
Patient journey research presents another challenge: different stakeholders see different parts of the experience.
A chronic lymphocytic leukemia (CLL) patient journey study integrated qualitative and quantitative perspectives across patients, caregivers, and HCPs. The resulting journey showed that patients do not necessarily move from diagnosis to treatment in a straight line, hey may experience uncertainty, revisit decisions, or encounter setbacks.
The work identified high-impact points where a patient support program could help, along with priority education, navigation and adherence needs.
Understand why communications work
The final use case focused on communications testing.
One study for a biosimilar manufacturer identified high- and low-performing messages across gastroenterology, rheumatology and dermatology, uncovering specialty-specific messaging opportunities.
Another study compared three direct-to-customers czema video creatives against a market leader’s creative. Using monadic testing, AI probing, patient video reactions and driver analysis, the research identified the strongest execution and guided improvements in benefit recall and differentiation.
Bringing speed, depth and richness together
The session reinforced that modernizing research isn’t about replacing traditional approaches or using AI for its own sake. When asked about gaining stakeholder buy-in for AI-supported approaches, Eltokhy recommended explaining how the technology works, showing examples and starting small before expanding to larger projects.
The speakers also emphasized security, compliance, privacy and keeping a human in the loop to interpret AI outputs and ensure quality.
As pharma teams face pressure to learn more, faster and more frequently, these examples show how conversational research can help uncover not only what is changing, but why.
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