In science, predicting the future is not a matter of crystal balls, but of data, technology and molecular knowledge. Now, thanks to modern biotechnology, we can detect subtle biological signals long before symptoms appear, before a treatment fails or even before a disease is triggered. What seemed like science fiction a decade ago is now a reality: anticipation is no longer magic, it is science.
21st century medicine and biology are shifting paradigms. It is no longer just about diagnosing what has happened, but about detecting what is about to happen.
The key lies in early biomarkers: messenger molecules, proteins, metabolites, DNA or RNA fragments that appear in subclinical stages, when there are no visible manifestations yet, but pathological processes have already begun,
These biomarkers allow:
Thanks to the evolution of biotechnology, we now have multiple platforms that allow us to analyse minute biological signals on a large scale and with very high sensitivity:
Using technologies such as RNA-seq or microarrays, it is possible to detect changes in the expression of regulatory genes long before a functional or morphological alteration becomes apparent.
Example: In melanoma patients, certain transcriptomic profiles predict the response to anti-Pd-1 immunotherapy even before the start of treatment.
The study of circulating proteins (such as cytokines, growth factors or acute phase proteins) or cellular metabolites allows the detection of early responses to infection, inflammation or toxicide.
Example: Detection of IL-& ferritin at elevated levels can anticipate cytokine storms in severe viral infections, as in COVID-19.
Epigenetic changes (such as DNA methylation) and the presence of circulating free DNA (cfDNA) allow detection of tumor processes even before they are visible by imaging.
Example: In oncology, liquid biopsies allow the detection of mutations in tumors at early stages, with applications in early detection, monitoring and selection of targeted therapies.
Using multi-parametric flow cytometry, mass cytometry (CyTOF) or single-cell RNA-seq, we can characterise the response of the immune system at the cellular level with unprecedented resolution.
Example: Identification of dysfunctional T-lymphocyte subpopulations that predict lack of response to immunotherapy in cancer.
Disease outbreak prevention
In public health, molecular surveillance platforms can detect emerging pathogens or viral variants even before symptoms spread in the population. This was key during the COVID-19 pandemic, and will remain so for future zonotropic diseases.
Personalised oncology
The use of predictive biomarkers allows stratification of patients: to know who will respond to immunotherapy, who needs combination therapy or who is at risk of relapse. This avoids unnecessary treatment and improves clinical outcomes.
Preventive medicine
In diseases such as multiple sclerosis, systemic lupus erythematosus or even Alzheimer’s, certain molecular profiles in blood or CSF make it possible to identify people at risk years before clinical diagnosis.
The future is anticipating
Predicting is not guessing. It is integrating molecular data, advanced bioinformatics and experimental validation to build a dynamic map of cellular and systemic health.
And while it may sound like magic… it is biotechnology: the ability to see the invisible, to hear biological signals before they become screams, and to act before it is too late.