- Asthma is characterised by chronic airway inflammation and bronchial hyperreactivity. Despite treatment with inhaled corticosteroids and bronchodilators, a proportion of patients do not achieve adequate asthma control.
- Several cytokines and growth factors involved in asthma-related inflammation interact with Janus Kinase 1 (JAK1). Londamocitinib is a potent and selective inhaled JAK1 inhibitor designed for the treatment of asthma.
- In this FIH study, oral inhalation of Londamocitinib had an acceptable safety and tolerability profile in healthy volunteers and asthmatic patients.
- A 50% reduction in mean FeNO was seen in asthmatic patients after 3 days, which persisted until the last dose.
- This preliminary data demonstrates anti-inflammatory effects in the lungs with minimal systemic exposure of Londamocitinib, supporting the rationale for further studies to investigate the clinical efficacy of londamocitinib in patients with asthma.
Archives: Agenda
AI-First Trials with Aika: How AI-Driven Operational Intelligence Is Changing Trial Execution
Protocol amendments, slow enrolment, and late feasibility surprises aren’t failures of science, they’re failures of execution. In this session, we’ll show how Aika, Biorce’s AI-driven clinical trials assistant, applies real-world operational evidence to trial design decisions before problems surface. The session includes a live demo of Aika, illustrating how teams can identify execution risk early and design more predictable, scalable trials.
CISCRP Perceptions & Insights Case Study
What Patients and the Public Think: Insights on AI and Tech in Trials
As AI and emerging technologies reshape the clinical research landscape, understanding the perceptions and experiences of trial participants, patients, and the public is critical to building trust and improving trial success when these tools are used. Drawing on the latest CISCRP Perceptions & Insights bi-annual survey of over 12,000 respondents globally, this session explores concerns, expectations, and trial experiences on the use of AI and decentralized trial technologies. Practical approaches to the planning and use of these tools in research will also be shared, aligned with emerging patient-centric regulatory and good practice expectations.
The Pursuit of Success: Driving your drug from the lab to the patient
- Defining what do we do well & what could be improved – EU vs US focus
- Planning & preparation within clinical trials – focus on phase 2/3
- Choosing the right trial designs for new inpatient studies
- How to achieve successful launch by building appropriate phase 3 program
Lunch and networking
Afternoon refreshments and networking with Apple Prize Draw
Morning refreshments and networking break
Resilience by Design: A Proactive Operational Framework for Clinical Trial Management
- Mapping critical risk points across the clinical trial lifecycle and identifying early operational signals before they escalate into issues
- Strengthening Sponsor–CRO–site collaboration through structured communication pathways and performance monitoring frameworks
- Shifting from reactive to proactive management by embedding contingency thinking throughout trial execution to safeguard timelines, data quality, and study outcomes
CASE STUDY: From Bench to Bedside: Building an End-to-End Biotech with an In-House Clinical Trial Unit
There are many aspects to moving from early research to clinical delivery under one roof. Using Ribocure as a case study, this session explores the practical realities of building clinical operations and establishing an in-house Phase II unit.
- Building and scaling a clinical operations function
- Talent, structure, and service provider strategy
- Establishing an in-house Phase II unit: key considerations and patient recruitment
Great expectations and how to meet them – Implementing AI into your study
- Understanding stakeholder expectations for AI in clinical research
- Practical steps for integrating AI into study design and operations
- Ensuring data quality, transparency, and regulatory compliance
- Measuring adoption, engagement, and return on investment from AI initiatives