Webinar Recap: Advances in Diagnostics

My colleague Justin Briggs and I had the wonderful opportunity to host Prime Movers Lab’s webinar on the field of diagnostics, primarily as it relates to single cell analysis, with three experts in the field, CEO of Zafrens Swamy Vijayan, CEO of Sampling Human Daniel Georgiev, and Chief Scientist of OraLiva John McDevitt. If you missed it you can watch the full conversation on our YouTube Channel. Here are some main takeaways from the conversation:

Recent technologies have enhanced our ability to observe complex human biology at the resolution of the single cell.

The rise of genomic sequencing — in particular, single-cell RNA sequencing (scRNA-seq) — has given scientists the capability to resolve our transcriptome, which refers to the RNA that is created from DNA, at the single-cell level. Other technologies help resolve our proteome (proteins translated from RNA) and epigenome (molecules that modify genetic material) on the single-cell level to provide a holistic but granular picture of the mechanisms at play relating to disease (e.g. mass spectrometry, ATAC-Seq and Hi-C). The belief that single-cell measurements will be as common and prevalent as PCRs is increasingly becoming a reality. Single cells, analyzed at scale, provide a wealth of new information — but what can we do with it?

The democratization of diagnostics has become a central theme in the field.

Often diagnostics are only available in resource-rich settings where equipment and personnel are integral to performing a diagnostic assay. However, all 3 panelists alluded to democratizing diagnostics, referring to the continual improvement and innovation to current technologies that allow diagnostics to be widely and routinely available. There is an increasing shift for diagnostics to be performed at the point of care (e.g., at a dentist’s office (OraLiva)) or for non-expert personnel to execute diagnostics pipeline (e.g., flow cytometry (Sampling Human)) or to be able to understand the relationship of molecular and functional states of cells at an extremely affordable and ultra-high throughput setting (e.g., 100,000 compound screen on a $5 glass slide within minutes (Zafrens)).

The integration of AI and diagnostics is inevitable.

Diagnostics, in a sense, is to make a prediction based on a given set of information, which is exactly what AI is created for. One new advantage is that we now have the infrastructure (i.e. cloud computing, advanced graphics processing units (GPU), and even quantum computing) to be able to handle large sums of data. Due to the abundant nature of cells, most datasets from single-cell analysis range in the millions of data points and require downstream computational analysis to extract actionable insights relating to disease.

Multimodal analysis will provide a more holistic understanding of mechanisms of action.

Omic analyses (studies relating to identifying molecular profiles) have been largely studied on a monomodal scale, meaning that we only capture a single portion of the entire biological process at any specific time. scRNA-seq, though powerful, only provides insight into the transcriptome. Recent studies have shown that transcripts do not always linearly get translated into protein as is often thought due to the central dogma of biology (i.e. DNA -> RNA -> Protein). Integrating all data types (i.e. multi-modal) will provide a much more comprehensive understanding of the state of disease and its associated mechanisms and pathways.

Prime Movers Lab invests in breakthrough scientific startups founded by Prime Movers, the inventors who transform billions of lives. We invest in companies reinventing energy, transportation, infrastructure, manufacturing, human augmentation, and agriculture.

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