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Sarovi Notes · Protocol

The patient model as infrastructure

Protocol is the biological baseline for a more personalized, preventive, and computational model of care.

February 4th, 20268 min readBiology

A patient baseline should be more than a PDF. It should be a computable starting point for prevention, risk, follow-up, and future therapy.

Protocol combines intake, blood signals, genomics, transcriptomics, biomarkers, and longitudinal follow-up. The goal is not to overwhelm the patient with raw data. The goal is to make biology usable for care.

Personalized medicine becomes practical when the patient baseline is living, longitudinal, and ready for computation.
WESWhole-exome sequencing gives a focused view of protein-coding variation that can matter for inherited risk, pharmacology, and rare disease clues.
WTSWhole-transcriptome sequencing can show gene-expression state and pathway activity, adding functional context beyond inherited sequence.
1000xSequencing costs have fallen by orders of magnitude since the first human genome era, opening the door to broader clinical use.
Example biomarker heatmap across molecular systems
immunemetabolicgenomicvascular M1M2M3M4M5M6 risk trajectory

From baseline to twin

The digital twin is not a single object. It is a patient representation that can absorb new evidence: imaging, blood work, treatment response, molecular assays, symptoms, and clinical notes.

Once that model exists, care can become more predictive. Follow-up becomes informed by change. Research can ask better questions from real patient signals.

A useful twin is not a decorative avatar. It is a structured set of patient vectors, trajectories, constraints, and signals that can be updated as the patient changes. Some parts are clinical: diagnoses, medication history, imaging, procedures, outcomes. Some parts are biological: variants, expression, proteins, biomarkers, immune state, metabolic state. Some parts are temporal: what changed, how fast, under what treatment, and with what uncertainty.

The report is not the product

Many genomics products end as a static report. That can be useful, but it is not enough for the model Sarovi is building. The baseline should become part of the operating system of care. It should inform preventive priorities, future diagnostic work, medication reasoning, trial matching, and research hypotheses.

Protocol is therefore not just a consumer wellness layer and not just a lab workflow. It is the biological input layer for Sarovi. The same patient baseline that helps explain risk today should also make future clinical and molecular analysis easier to run, compare, and revisit.

Sequencing shifted from rare research event toward computable clinical input
early genome eraroutine computation era 2001200820152024
Source pack

How to explain a patient baseline without pretending certainty.

Good education has to show three things at once: what we know, what we do not know, and what would change the clinical decision. A biological baseline only becomes useful when it is joined to time, symptoms, and clinician oversight.

NHGRI cost data Nature: personalized medicine

The scientific challenge is to keep uncertainty visible. Sarovi should never pretend that a biomarker is destiny. The goal is to preserve signal, context, and probability so clinicians and patients can make better decisions earlier.

References

  1. National Human Genome Research Institute, DNA Sequencing Costs Data, historical sequencing-cost trends.
  2. European Commission, European Health Data Space, health data access and reuse context for care and research.
  3. Nature Portfolio, Personalized medicine topic collection, ongoing research context for personalized and precision medicine.