From the moment a new technology is born in the laboratory to the day it actually helps patients, it often takes years – sometimes decades.
The problem, however, is not a lack of good ideas, but that a scientific breakthrough must survive the real world: standards, regulations, the market and, most importantly, trust.
Georges Dubourg , a researcher in the field of biomedical technologies and Organ-on-a-Chip systems , spoke about those “invisible” phases of science – those between discovery and application – at the event “Open Studio Europe: What does it mean to do science today?” , held in the organization of the European House Novi Sad and the French Institute Novi Sad.
From the moment a technology is developed in the laboratory to its potential application in medicine, years often pass. Based on your experience, which stages of that journey are the most critical and where does the transition from research to practice most often get “stuck”?
From the first laboratory evidence that a technology works to its reliable use in medicine, a long period of time is rarely due to a lack of good ideas. Much more often it arises from the requirements of real application: a clearly defined purpose, stable and repeatable performance, as well as the ability of the technology to function safely and predictably outside the framework in which it was developed by its authors.
On that way, the transition is most often stuck in the so-called the gap between validation and standardization – at the stage when the results are promising but not yet sufficiently reliable or comparable for routine use. In the first stage of that gap, early prototypes may look impressive in the hands of one expert team, but fail when others try to replicate the results. For a technology to be truly trusted, it must deliver consistent results regardless of who uses it, in which lab, and in what environment.
In the second stage, even when the method is reproducible, it is necessary to translate it from the “prototype” phase to the “product” phase – with clear quality control, appropriate documentation and fitting into real work processes. In the end, technology adoption depends less on the excitement of the first successful experiment and more on the ability to get the same, reliable result every time – and in different hands.
When it comes to organ-on-a-chip technologies, where do you see their real potential today? What can they already change in drug development, and what expectations, in your opinion, are premature or wrongly set?
Today, realistically speaking, organ-on-a-chip systems (a technology that uses a microfluidic chip to mimic the physiological function of an individual organ) can already significantly improve the early selection of drug candidates and certain safety assessments, as a supplementary source of evidence, especially in areas where animal models often give a wrong picture. They are particularly useful in the investigation of barrier functions, inflammatory pathways, certain aspects of cardiotoxicity and toxicity related to human metabolism.
Their value lies not only in showing that a compound does not work, but also in explaining why it fails. This allows research teams to make better quality decisions earlier and avoid expensive surprises in later stages of development. What is still premature, however, is the expectation that these technologies will completely replace animal testing for all parameters in the near future, or that organ-on-a-chip systems are viewed as universal and reliable predictors of clinical efficacy.
The field is evolving towards more complex platforms such as multi-organ systems, AI-assisted analysis, and long-term visions that include models tailored to individual patients. However, the realization of that potential will depend on further progress in standardization, reproducibility, validation and practical application on a larger scale.
In the development of such technologies, how are the needs of patients, the demands of the pharmaceutical industry and the regulatory framework aligned, and where do scientists have the least and where the most influence in that triangle?
In this triangle , patients, industry and regulators are the three pillars that hold translational technology together. Each of them has different success criteria: patients and the general public strive for relevance and safety, industry for speed of development, scalability and easy integration into existing processes, while regulators insist on validated performance, transparency and clear guidelines for the interpretation of results and their limitations. Real alignment occurs when all three actors focus on a clearly defined goal and when evidence is systematically built precisely in relation to that goal.
Scientists in that triangle have a specific and key role: their greatest influence lies in shaping the scientific plausibility of technology . They determine the level of biological plausibility, select relevant outcomes, set controls, and define standards of experimental rigor that ultimately build the credibility of the entire technology. Wider acceptance, however, also depends on practical and organizational factors – available resources, institutional priorities and the readiness of the system to change established practices. This does not diminish the importance of science, but indicates that success is achieved only at the combination of solid evidence and appropriate systemic incentives.
What does the development of high technologies look like in a country like Serbia? What challenges are specific to a smaller scientific and market environment, and what advantages can such a context bring compared to larger and more developed systems?
In smaller environments like Serbia, key challenges include limited local market demand, fewer industrial partners for joint development, and the complex transition from research funding to product commercialization. Talent retention is often difficult , as experienced engineers and translational scientists are highly mobile in the global labor market. Additionally, many validation processes require international collaborative networks, especially when confidence in the technology depends on multi-site studies and globally recognized standards.
On the other hand, smaller ecosystems can have important advantages. Teams are often more connected, collaboration is more immediate, and decisions can be made faster when the right partnerships exist. Early stage development costs are often lower, and strong technical groups can build highly competitive R&D and prototyping capabilities.
A particularly effective strategy for Serbia is early internationalization: establishment of cooperation related to the EU , validation of technologies in several locations abroad and orientation towards the global market, while maintaining key research and development capacities in the country. In such a model, the local ecosystem becomes the backbone for speed and technical excellence, while scale, validation and market access are achieved through international integration.