Five broad, overlapping eras, recorded in keywords. The dates mark shifts in how Ayurvedic knowledge was kept, taught, tested and regulated.
Nighantus catalogues · Rasashastra traditions · Powders, decoctions, oils, pastes
Some mineral and metal preparations can carry hazardous amounts of lead, mercury or arsenic.
Practitioner lineages · Manuscripts and printed books · Local dispensaries · Household remedies
Practice and materials differed by region and by lineage.
College curricula · Hospitals · Pharmacopoeial work · Regulated manufacturing
Standardisation does not automatically establish clinical effectiveness.
Medicinal-plant programmes · Research databases · Department of AYUSH, 2003
Findings differ by treatment and by study quality.
Ministry of AYUSH, 2014 · WHO benchmarks, 2022 · International terminology, 2023 · Pharmacovigilance
Clinical decisions should consider evidence, contraindications, interactions and patient safety.
Ayurveda has described differences in constitution, diet, and daily routine for three millennia. Modern research asks how these observations relate to measurable differences in human biology.
AyurHack brings that research together. We explore Prakriti, the Ayurvedic concept of constitutional baseline, through genetics, metabolomics, and chronobiology. Each claim links to a source, with its limitations made clear.
Read the scientific ledgerAyurveda distinguishes your constitutional baseline, Prakriti, from your current state, Vikriti. Diet, sleep, stress, and illness can change the latter.
Your fixed psycho-physiological type, set at conception from the relative proportion of Vata, Pitta and Kapha (the tridosha), genetically anchored (shukra-shonita) and stable across life, the way a genotype is stable.
Your current deviation from that baseline, driven by diet, season, stress, sleep debt, illness. Vikriti is what a symptom actually reports; treatment in Ayurveda targets closing the gap back toward Prakriti.
Genotype-informed risk before disease onset.
Constitution-matched diet, routine, and season protocols.
Ahara, Dinacharya and drug response tuned to Prakriti, not population averages.
Self-observation (Vikriti tracking) closes the feedback loop.
Since 2008, CSIR‑IGIB's TRISUTRA program and independent groups have studied associations between Prakriti and molecular variation. These five correlates come from cohort studies; the cards include findings, methods, and non-replication results.
A liver enzyme that clears roughly a tenth of common prescription drugs. In a 132‑person genotyping study, 91% of Pitta‑Prakriti individuals carried fast‑metabolizer genotypes, while poor‑metabolizer genotypes were 2.5–3.4× more frequent in Kapha, lining up with the classical claim that Pitta runs a "fast" metabolism and Kapha a "slow" one.
PCR‑RFLP genotyping, n=132 healthy adults. *2/*3 poor‑metabolizer genotype: OR 3.5 in Kapha vs. Vata/Pitta (p=0.008). A later n=351 epilepsy cohort testing phenytoin clearance found no significant CYP2C19–Prakriti association. The finding has not replicated in a clinical population.
A gene sitting at the crossroads of five energy‑metabolism pathways: glycolysis, gluconeogenesis, galactose and starch/sucrose metabolism. In a genome‑wide scan this variant tracked specifically with Pitta, the type classical texts describe as having the sharpest digestive fire (Agni) and fastest energy turnover.
Affymetrix 6.0 GWAS-style scan, 262 well‑classified individuals screened from 3,416 subjects; replicated by Sanger sequencing in 665 individuals (p=2.06×10⁻² vs Vata, p=6.16×10⁻³ vs Kapha). SIFT‑predicted damaging (score 0.01).
An oxygen-sensing gene that controls how the body responds to low‑oxygen environments. The high‑expression variant was more common in Kapha types and tracked with high‑altitude pulmonary edema risk, while Pitta types, and populations native to high altitude, carried it far less often.
Published in PNAS, 2010. The first Prakriti finding to be replicated functionally: the same EGLN1 locus independently distinguishes Tibetan and Andean high‑altitude‑adapted populations from lowlanders, giving the Prakriti‑based subgroup discovery external convergent validity.
Flow‑cytometry markers for activated B‑cells (CD25) and natural killer cells (CD56). Kapha‑Prakriti individuals showed significantly elevated levels of both, a candidate molecular basis for the classical description of Kapha as the most immunologically resilient constitution.
n=222 healthy subjects (95 Kapha, 57 Pitta, 70 Vata), ANOVA p<0.05. Independently replicated in a 2023 rheumatoid‑arthritis case‑control study, where Kapha‑predominance was protective (OR 0.27, 95% CI 0.15–0.47).
Ahara, the Ayurvedic approach to food, considers constitution and meal timing. Ayurnutrigenomics studies how these ideas relate to metabolic pathways and nutrient-gene expression.
| Prakriti | Classical Ahara logic | Metabolomic signature observed | Functional direction |
|---|---|---|---|
| VATA | Warm, moist, grounding foods counter Vata’s light/cold/mobile qualities | Variable lipid & purine handling; downregulated cellular ketone metabolism relative to Pitta | Regular meal timing, warming spices, healthy-fat density |
| PITTA | Cooling, moderate foods counter Pitta’s heat/sharpness | Upregulated BCAA (valine/leucine/isoleucine) turnover, retinoid & estrogen metabolic pathways | Portion moderation, reduced fermented/acidic load, earlier meal timing |
| KAPHA | Light, warm, stimulating foods counter Kapha’s heavy/slow qualities | Downregulated carbohydrate, lipid & glucuronidation metabolism vs. Pitta | Lower caloric density, pungent/bitter emphasis, activity-linked meal timing |
Metabolomic column summarizes plasma-metabolomics profiling across classified Prakriti groups (functional-pathway enrichment, not individual biomarker cutoffs). These findings generate hypotheses, not diagnostic thresholds.
Dinacharya describes recurring dosha windows throughout the day. The clock compares traditional routines with modern circadian observations. Overlapping times do not establish clinical benefit.
Pre-dawn Vata window. Classically the optimal rise time; overlaps the anticipatory rise in cortisol that begins ~2h before habitual waking.
Nine questions about body traits, physiology, and behavior, based on domains used by AyuSoft and CCRAS-PAS. This is an educational demo, not a validated assessment.
Join the waitlist for daily guidance based on your constitutional profile.
The studies below report molecular associations, assessment validation, and findings that did not replicate. No Prakriti-stratified human randomized controlled trials have been published to date.
Genotyped or metabolomically profiled human cohorts, case-control or GWAS-style, peer-reviewed.
Flow-cytometry or clinical case-control studies linking Prakriti to measurable cell/marker data.
Diagnostic-accuracy studies testing assessment-tool agreement against expert clinicians.
Peer-reviewed synthesis papers connecting mechanisms across studies; not primary data.
Non-replications, null results, or scoping reviews flagging validation limits.
Zero published randomized controlled trials test Prakriti-stratified intervention outcomes head-to-head. Every genomic and immune correlate here is associative, cross-sectional cohort data.
Of 64 Prakriti-assessment instruments reviewed across the literature, only 2 (CCRAS-PAS, ACPI) meet 7 of 9 standard psychometric validation criteria.
CYP2C19–Prakriti association, robust in a 132-person cohort, was absent in a 351-person clinical phenytoin study. Sample composition and clinical vs. healthy populations plausibly explain the gap, but it isn't settled.
