Bio

Sharada Kalanidhi is Director of Data Science at Stanford Genome Technology Center, SGTC (Dept of Biochemistry), Stanford University School of Medicine. Prior to joining Stanford, she spent 20+ years in industry in leadership roles across quantitative strategy, platform development, data science and statistics. Her experiences shape her multi-disciplinary outlook and approach.

A decade of her experience was in Wall Street, where she developed the mathematical algorithms underlying pricing, trading and portfolio strategies for complex high-risk instruments such as interest rate derivatives and mortgages. She led teams that built “decision engine” platforms that managed the portfolio risk of such instruments under various scenarios. When a family member developed symptoms of unexplained fatigue, she became drawn to biostatistical problems. She collaborated with researchers at SGTC on data science and statistical analysis on ME/CFS patients and subsequently joined them full-time.

Her recent research has involved multivariate and machine learning analysis of the genomics, proteomics and metabolomics underlying ME/CFS, and post-viral fatigue syndromes including Long Covid. More broadly, her research interests lie at the intersections of biology, chemistry and (pure) mathematics. She is an inventor on several granted US patents.

Current Role at Stanford

Paraphrasing the mathematician Alexander Grothendieck: the essential thing is to pose problems in the right framework.

Sharada is developing a new field, Mathematical Medicine, which applies pure mathematical frameworks to genomic and multi-omic data for quantitative, personalized diagnosis. Her work addresses a fundamental challenge in contemporary medicine: prevailing cohort-based diagnostic approaches are not always equipped to capture the biological mechanisms relevant to individual patients, particularly in long-pending, complex “outlier” cases.

After more than a decade of research and close collaboration with biochemists at the Stanford Genome Technology Center (Dept. of Biochemistry), Sharada concluded that the mathematics currently used for multi-omic diagnosis is not sufficient for the level of biological and clinical complexity being attempted, particularly for individual patients who lack relevant statistical cohorts. Her conclusion echoes the perspective of the mathematician Mikhail Gromov: “This area does not yet exist. It will have to be invented.” This gap has important clinical consequences: individual biological differences may be treated as “noise” or as "outliers" rather than as clinically meaningful information. As a result, many patients with complex or multi-system conditions remain undiagnosed or incorrectly diagnosed, sometimes for decades, delaying effective treatment and, in some cases, allowing disease processes to worsen.

Mathematical Medicine addresses these limitations by developing an intermediate translational layer between cohort-based statistical models and individualized multi-omic diagnosis and clinical decision-making. The approach reflects the data-first philosophy articulated by the late mathematician Jim Simons: “We don’t start with models. We start with data. We don’t have any preconceived notions.” By developing new mathematical frameworks for interpreting an individual’s genomic and multi-omic data, Mathematical Medicine seeks to seeks to let the data speak for itself while enabling quantitative, individualized diagnosis and clinical decision-making.

Sharada’s research has led to the diagnosis and identification of appropriate treatment pathways for patients with previously undiagnosed, complex conditions. These rare and atypical cases also reveal biological relationships not apparent in population-level analyses, leading to insights that can inform broader research, clinical applications, and drug development.

Further information on this field, including opportunities for early philanthropic partnerships, is available at: https://mathmed-2026.web.app

Patents

  • "United States Patent 8996510 Identifying digital content using bioresponse data", Mar 31, 2015
  • "United States Patent 8719278 Method and system of scoring documents based on attributes obtained from a digital document by eye-tracking data analysis", May 6, 2014
  • "United States Patent 8509826 Biosensor measurements included in the association of context data with a text message", Aug 13, 2013

Links

All Publications

  • Immunoglobulin G complexes from post-infectious ME/CFS, including post-COVID ME/CFS disrupt cellular energetics and alter inflammatory marker secretion. Brain, behavior, & immunity - health Liu, Z., Hollmann, C., Kalanidhi, S., Lamer, S., Schlosser, A., Basens, E. E., Nikolayshvili, G., Sokolovska, L., Riemekasten, G., Rust, R., Bellmann-Strobl, J., Paul, F., Naviaux, R. K., Nora-Krukle, Z., Sotzny, F., Scheibenbogen, C., Prusty, B. K. 2026; 52: 101187

    Abstract

    Autoimmunity is a key clinical feature in both post-infectious Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and Post-Acute Sequelae of COVID (PASC). Passive transfer of immunoglobulins from patients' sera into mice induces some clinical features of PASC. However, the physiological effects of immunoglobulins on cellular alterations remain elusive. In this study, we tested the potential effects of immunoglobulins from ME/CFS patients on endothelial cell dysfunction.We have isolated immunoglobulins from 106 individuals, including ME/CFS (n = 39), PCS-CFS (n = 15), MS (n = 20) patients, and healthy controls (n = 41). Protein composition of the isolated immune complexes was studied using mass spectrometry. The effect of isolated immune complexes on mitochondria was evaluated using confocal microscopy and a Seahorse XFe96 Extracellular Flux Analyzer, and the impact on inflammatory cytokine secretion was studied using a multiplex bead-based assay.Here, we demonstrate that IgG isolated from post-infectious ME/CFS patients selectively induces mitochondrial fragmentation in human endothelial cells and alters cellular energetics. This effect is lost upon cleavage of IgG into its Fab and Fc fragments. The digested Fab fragment from ME/CFS alone was able to alter the cellular energetics, resembling the effect of intact IgG. IgG from post-infectious ME/CFS, including post-COVID ME/CFS patients, induced distinct but separate cytokine secretion profiles in healthy PBMCs. Proteomics analysis of IgG-bound immune complexes revealed significant changes in immune complexes from ME/CFS patients, affecting extracellular matrix organization, whereas those from post-COVID ME/CFS patients pointed to alterations in hemostasis and blood clot regulation.We demonstrate that IgGs from ME/CFS patients carry a chronic protective stress response that promotes mitochondrial adaptation via fragmentation, without altering mitochondrial ATP generation capacity in endothelial cells. Together, these results highlight a potential pathogenic role of IgG in post-infectious ME/CFS and point to novel therapeutic strategies targeting antibody-mediated metabolic dysregulation.

    View details for DOI 10.1016/j.bbih.2026.101187

    View details for PubMedID 41704659

    View details for PubMedCentralID PMC12907502

  • Increased circulating fibronectin, depletion of natural IgM and heightened EBV, HSV-1 reactivation in ME/CFS and long COVID. medRxiv : the preprint server for health sciences Liu, Z., Hollmann, C., Kalanidhi, S., Grothey, A., Keating, S., Mena-Palomo, I., Lamer, S., Schlosser, A., Kaiping, A., Scheller, C., Sotzny, F., Horn, A., Nürnberger, C., Cejka, V., Afshar, B., Bahmer, T., Schreiber, S., Vehreschild, J. J., Miljukov, O., Schäfer, C., Kretzler, L., Keil, T., Reese, J. P., Eichner, F. A., Schmidbauer, L., Heuschmann, P. U., Störk, S., Morbach, C., Riemekasten, G., Beyersdorf, N., Scheibenbogen, C., Naviaux, R. K., Williams, M., Ariza, M. E., Prusty, B. K. 2023

    Abstract

    Myalgic Encephalomyelitis/ Chronic Fatigue syndrome (ME/CFS) is a complex, debilitating, long-term illness without a diagnostic biomarker. ME/CFS patients share overlapping symptoms with long COVID patients, an observation which has strengthened the infectious origin hypothesis of ME/CFS. However, the exact sequence of events leading to disease development is largely unknown for both clinical conditions. Here we show antibody response to herpesvirus dUTPases, particularly to that of Epstein-Barr virus (EBV) and HSV-1, increased circulating fibronectin (FN1) levels in serum and depletion of natural IgM against fibronectin ((n)IgM-FN1) are common factors for both severe ME/CFS and long COVID. We provide evidence for herpesvirus dUTPases-mediated alterations in host cell cytoskeleton, mitochondrial dysfunction and OXPHOS. Our data show altered active immune complexes, immunoglobulin-mediated mitochondrial fragmentation as well as adaptive IgM production in ME/CFS patients. Our findings provide mechanistic insight into both ME/CFS and long COVID development. Finding of increased circulating FN1 and depletion of (n)IgM-FN1 as a biomarker for the severity of both ME/CFS and long COVID has an immediate implication in diagnostics and development of treatment modalities.

    View details for DOI 10.1101/2023.06.23.23291827

    View details for PubMedID 37425897

    View details for PubMedCentralID PMC10327231

  • Off label use of Aripiprazole shows promise as a treatment for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): a retrospective study of 101 patients treated with a low dose of Aripiprazole. Journal of translational medicine Crosby, L. D., Kalanidhi, S., Bonilla, A., Subramanian, A., Ballon, J. S., Bonilla, H. 2021; 19 (1): 50

    View details for DOI 10.1186/s12967-021-02721-9

    View details for PubMedID 33536023