PharmaMar and Globant Bring AI to Oncology Research, Underscoring the Build-vs-Partner Reality

PharmaMar’s AI collaboration with Globant is a useful reminder that the future of AI in drug development will not be dominated solely by the largest pharmaceutical companies. Many biopharma organizations want the benefits of AI-enabled oncology research without taking on the full burden of building internal models, platforms, and engineering teams from scratch. For them, strategic partnerships are becoming the pragmatic route.

That is especially true in oncology, where biological complexity and competitive pressure create strong incentives to improve target selection, biomarker strategy, and molecule prioritization. Companies focused on niche expertise may be well positioned to benefit from AI if partners can help embed it into decision-making rather than leaving it as a detached analytics exercise. The operational fit matters more than the sophistication of the technology alone.

The partnership also speaks to a segmentation emerging in the market. Large pharma may concentrate on proprietary foundation models and massive internal data platforms, while smaller or more specialized players pursue modular partnerships tailored to particular disease areas or workflow problems. That does not necessarily create a capability gap; in some cases, focused deployment can produce faster returns than broad platform ambition.

As AI procurement in life sciences matures, collaborations like this may become more common than all-in platform builds. The winners will likely be those that align AI with a clear scientific bottleneck and measurable business objective, rather than adopting it as a general innovation signal.