What I Confirmed in San Diego
Last week, I attended the AACR 2026 Annual Meeting. Every year when I attend this conference, I carry one question with me: "Where does spatial biology stand right now?"
This year, the answer was clear. Spatial biology is no longer "an interesting new technology." What I felt across countless posters and oral presentations was that spatial transcriptomics and spatial proteomics are becoming not a variable, but a constant in cancer research.
It was evident everywhere — used in basic research to reveal the structure of the tumor microenvironment, and increasingly established as a tool to explain treatment response and resistance in clinical research. In this post, I will organize the three key currents I captured at AACR 2026, through the lens of a CMO.
1. Evolution of Technology: Broader, Deeper, at Scale
One of the most noteworthy technical announcements at this year's AACR was the unveiling of Atera, the next-generation platform from 10x Genomics. Atera is a platform capable of obtaining whole-transcriptome-level information across larger tissue areas with greater efficiency than ever before.
The significance of this announcement is not simply about improved technical specifications. It is because Atera could serve as a practical solution to the two walls spatial transcriptomics has not yet been able to breach — large cohort studies and clinical biomarker development.
Until now, spatial transcriptomics has excelled at performing deep analyses on a small number of samples. But to demonstrate clinical significance, consistent patterns must be shown across cohorts of dozens to hundreds of patients. The emergence of platforms like Atera provides the technological foundation to bridge this gap.
In fact, at this year's AACR, I was struck by the impression that ST on TMA (Tissue Microarray) approaches are becoming nearly routine. Numerous presentations featured research designs where dozens to hundreds of patient samples were spatially profiled simultaneously on TMA, demonstrating that spatial biology is moving beyond exploratory study into the phase of confirmatory study.
2. Spatial Biology × Drug Response: From Observation to Therapeutic Connection
The most prominent trend I felt at this AACR was the rapid growth of research that no longer uses spatial transcriptomics merely as a tool to understand biology, but directly links it to drug response.
This trend was especially striking in the ADC and immuno-oncology (IO) space.
1) ADC: Reading Resistance Through Spatial Pharmacokinetics
Portrai presented two studies at this year's AACR. One of them was a study that used spatial transcriptomics to identify pharmacokinetic barriers and tumor-intrinsic resistance determinants in a cohort of breast cancer patients treated with a HER2-targeting ADC.
The key points that drew attention were:
The spatial distance between vasculature and target was shown to be directly associated with ADC delivery efficiency in a patient cohort
Spatial heterogeneity of HER2 expression — even among tumors with the same H-score, ADC response differed between cases where HER2 was uniformly distributed versus patchily distributed
A multi-dimensional analysis based on spatial patterns and spatial distances, rather than the conventional single-biomarker approach (H-score, IHC), could predict response/resistance more precisely
At the venue, many researchers found the approach of "linking ST with ADC analysis" itself to be remarkably fresh. In particular, the spatial variables connecting vessel distance and target expression heterogeneity to ADC response/resistance drew many questions and resonance from pharma researchers.
This was also a real-patient-data validation of the concept of "same target, different destiny" that I discussed in the March blog.
2) IO: Dissecting the Spatial Architecture of Resistance
The second study identified core resistance niches distinguishing non-MPR (major pathological response) from MPR in NSCLC after neoadjuvant chemoimmunotherapy, using spatial transcriptomics.
This study analyzed the spatial architecture of residual tumors after treatment and identified unique resistance niches observed only in non-MPR cases. Critically, these niches were defined not by a single cell type or a single gene, but by the spatial arrangement and distance relationships of specific cells.
There were many questions at the venue about distance-based interpretation. It was a moment confirming that the concepts of "distance and boundary" I introduced in the February blog are functioning as a core grammar for explaining treatment resistance in actual research.
What pharma researchers focused on most was the possibility that understanding the spatial architecture of resistance could be directly applied to next-step therapy development. Knowing not just "which cell creates resistance" but "which spatial structure creates resistance" provides far more actionable information for designing the next therapeutic strategy.
3. New Approach Methodologies (NAM): From In Vitro to In Silico
Another impressive aspect of AACR 2026 was the resolute direction from both academia and regulatory bodies regarding NAM (New Approach Methodologies).
The organoid and organ-on-a-chip fields have seen remarkable advances over the past year, and at this conference, an exceptionally large number of posters were presented linking co-culture systems with drug response evaluation. A dedicated major session on NAM was organized, where the commitment of the FDA and academia to advance in this direction was unmistakable.
The point where this trend meets spatial biology is fascinating. Research is emerging that spatially analyzes drug response in organoids and organ-on-a-chip systems, and attempts to build a translational bridge by comparing these results with spatial data from actual patient tissues.
When NAM, spatial biology, and in silico modeling converge, we will move toward an era where we can simultaneously understand and predict drug action across three axes: patient tissue (in vivo) → in vitro models → virtual simulation (in silico).
What I Felt on the Ground: The 'Clinical Maturation' of Spatial Biology
If I were to summarize AACR 2026 in one phrase, it would be that spatial biology is becoming 'clinically mature.'
Several concrete signals support this:
Technology: With the emergence of next-generation platforms like Atera, whole-transcriptome-level information can now be obtained efficiently across larger tissue areas. ST on TMA approaches are becoming routine, making large cohort studies a reality.
Research: Spatial transcriptomics is no longer confined to understanding biology — research directly applying it to predicting treatment response and elucidating resistance mechanisms is surging. Across diverse modalities including ADC and IO, spatial analysis is establishing itself as a key explanatory variable for drug response.
Industry: Pharma researchers are beginning to recognize spatial data not as mere academic curiosity, but as information practically needed for next-step therapy development and clinical trial design.
Regulatory: The FDA's clear direction on NAM and in silico evidence suggests that spatial biology-based predictive models could play a role within future regulatory frameworks.
Looking Ahead
What this AACR confirmed is that spatial biology is becoming an essential analytical framework tightly coupled with diverse drug modalities — IO, ADC, bispecific antibodies, RPT.
Next-generation technologies like Atera, large-scale studies through ST on TMA, and direct linkage with therapeutic response. At the intersection of these three, spatial biology is evolving beyond a mere observational tool into a language that changes drug development decision-making.
In the March blog, I wrote that "the next language of ADC development is space." At AACR 2026, I met researchers who have already begun to speak that language. This current will accelerate further next year, and Portrai will continue to demonstrate the clinical value of spatial biology at the center of this movement.
References
Portrai, AACR 2026 Poster. Spatial Transcriptomics uncovers pharmacokinetic barriers and tumor-intrinsic determinants of resistance to trastuzumab deruxtecan in breast cancer.
Portrai, AACR 2026 Poster. Spatial Transcriptomics reveals core resistance niches distinguishing non-MPR from MPR in NSCLC after neoadjuvant chemoimmunotherapy.
