Gene regulation and gene discovery
1992 – 1999Kennedy's first research programme ran from insulin gene transcription to disease gene discovery. As a postdoctoral scientist in William J. Rutter's laboratory at UCSF she identified Pur-1, a zinc-finger transactivator of the insulin promoter (PNAS, 1992), and showed that the minisatellite at the type 1 diabetes locus IDDM2 regulates insulin transcription (Nature Genetics, 1995). At Millennium Pharmaceuticals she implemented genomic and genetic approaches to uncover diabetes susceptibility genes, and at Chiron Corporation she led colon and breast cancer gene discovery efforts that identified oncology markers for therapeutic drug development.123456
- Insulin gene transcription
- Type 1 diabetes genetics
- Diabetes susceptibility genes
- Colon and breast cancer markers
Organisations
- University of California, San Francisco · SAN FRANCISCO, CALIFORNIA
- Millennium Pharmaceuticals, Inc.
- Chiron Corporation
Publications
- 1995 The insulin gene promoter. A simplified nomenclature Diabetes
- 1995 The minisatellite in the diabetes susceptibility locus IDDM2 regulates insulin transcription Nature Genetics
- 1992 Pur-1, a zinc-finger protein that binds to purine-rich sequences, transactivates an insulin promoter in heterologous cells Proceedings of the National Academy of Sciences of the United States of America
Chapters
- Education and training · CHAPTER 01 · 1992 – 1995
- Millennium Pharmaceuticals · CHAPTER 02 · 1999 – 1999
- Chiron Corporation · CHAPTER 03 · 1999 – 1999
Whole-genome genotyping platforms
JAN 2000 – MAR 2008At Affymetrix, where she was a Senior Director from January 2000 to March 2008 leading the Genomics Collaborations and Genotyping Technology R&D groups, Kennedy's teams published the methods that made array-based SNP genotyping practical: "Large-scale genotyping of complex DNA" (Nature Biotechnology, 2003, first author), the one-primer 10K assay (Genome Research, 2004), the 100K array set (Nature Methods, 2004) and the genotype-calling algorithms in Bioinformatics (2003, 2005). She is a co-inventor on the Affymetrix patent "Method for genotyping polymorphisms in humans".547891011
- SNP genotyping
- Genome-wide association studies
- HapMap-era human genetics
- Copy-number detection
Organisations
Technologies
- Affymetrix GeneChip Mapping arrays · PLATFORM
High-density oligonucleotide arrays for genotyping single-nucleotide polymorphisms genome-wide. The 10K array genotyped over 10,000 SNPs per individual on a single array (Genome Research, 2004) and the 100K set scored 116,204 SNPs on a pair of arrays with call rates above 99% (Nature Methods, 2004). A 2006 NHGRI primer cites "Kennedy et al, Nature Biotech, 2003" as the reference for the GeneChip Mapping Assay, and Kennedy is a co-inventor on Affymetrix's US 7,300,788, "Method for genotyping polymorphisms in humans".
- Whole-genome sampling analysis (one-primer genotyping assay) · METHOD
The sample-preparation method behind the GeneChip Mapping arrays: restriction digestion fractionates the genome, a specific fractionated subset is amplified with a single primer, and alleles are read by allele-specific hybridization to the array. Described in "Parallel Genotyping of Over 10,000 SNPs Using a One-Primer Assay on a High-Density Oligonucleotide Array" (Genome Research, 2004), on which Kennedy is a co-author, and introduced in "Large-scale genotyping of complex DNA" (Nature Biotechnology, 2003), on which she is first author.
Publications
- 2005 Dynamic model based algorithms for screening and genotyping over 100K SNPs on oligonucleotide microarrays Bioinformatics
- 2004 Parallel Genotyping of Over 10,000 SNPs Using a One-Primer Assay on a High-Density Oligonucleotide Array Genome Research
- 2003 Algorithms for large-scale genotyping microarrays Bioinformatics
- 2003 Large-scale genotyping of complex DNA Nature Biotechnology
Chapters
- Affymetrix · CHAPTER 04 · JAN 2000 – MAR 2008
- Whole-genome genotyping · CHAPTER 05 · 2003 – 2005
Thyroid nodule genomic classification
APR 2008 – DEC 2022The programme that defined Veracyte, where Kennedy was Chief Scientific Officer from 2008 and Chief Medical Officer from 2018. The Afirma Gene Expression Classifier was developed from 315 nodules (JCEM, 2010), launched in January 2011 and validated prospectively in 3,789 patients (NEJM, 2012). The RNA sequencing-based Afirma GSC followed in 2017, validated in JAMA Surgery (2018) with at least one third more benign calls than the original test, and was extended with the Xpression Atlas of variants and fusions, Hürthle cell and medullary thyroid carcinoma classifiers. By January 2018 Veracyte had performed 100,000 Afirma tests.5121314151617
- Indeterminate thyroid fine-needle aspirates
- Avoiding diagnostic thyroid surgery
- Hürthle cell nodules
- Medullary thyroid carcinoma
- Variant and fusion reporting
Organisations
- Veracyte, Inc. · SOUTH SAN FRANCISCO, CALIFORNIA
Technologies
- Afirma Gene Expression Classifier · PRODUCT
Veracyte's first commercial product, launched in January 2011 as the Afirma Thyroid FNA Analysis. It combines cytopathology with a gene expression test, described in trade press as a 142-gene signature, to identify benign nodules among thyroid fine-needle aspirates that cytology leaves indeterminate. Developed from 315 nodules and more than 247,186 transcripts (JCEM, 2010) and validated prospectively at 49 sites in 3,789 patients (NEJM, 2012), with Kennedy as last and second author respectively.
- Afirma Genomic Sequencing Classifier · PRODUCT
The second-generation Afirma test, built on whole-transcriptome RNA sequencing and ensemble machine learning algorithms. Veracyte announced pivotal validation data on May 4, 2017 and began transitioning patients to the GSC that quarter, saying it could save an estimated 70% of patients with benign nodules from unnecessary surgery. The JAMA Surgery validation (2018) found it identifies at least one third more benign nodules than the original test with 91% sensitivity. The companion Afirma Xpression Atlas, launched May 2018, reports gene variants and fusions from the same sample.
- Whole-transcriptome RNA sequencing · PLATFORM
The sequencing platform that replaced microarrays in Veracyte's second-generation tests. Kennedy described it at the 2018 Xpression Atlas launch: "Our RNA sequencing-based platform enables us to derive unprecedented amounts of rich genomic content from clinical samples." The Afirma GSC, Percepta GSC and Envisia classifiers are built on it, and PinkDx applies whole-transcriptome sequencing to vaginal swab samples in its endometrial cancer programme.
- Ensemble machine learning classifiers · METHOD
The algorithmic approach behind Veracyte's sequencing-era classifiers and PinkDx's swab test. Kennedy said in 2017 that "the ensemble machine learning algorithms, which underlie the performance of Afirma GSC, derive from years of thoughtful scientific research, data analysis and statistical modeling", and that the company was "employing the same machine learning methods that are being used in other fields such as social media and self-driving cars". The 2019 BMC Systems Biology paper, with Kennedy as last author, describes a trio of machine learning algorithms for Hürthle cell nodules.
Publications
- 2022 Preoperative Identification of Medullary Thyroid Carcinoma (MTC): Clinical Validation of the Afirma MTC RNA-Sequencing Classifier Thyroid
- 2021 Afirma Genomic Sequencing Classifier and Xpression Atlas Molecular Findings in Consecutive Bethesda III-VI Thyroid Nodules The Journal of Clinical Endocrinology & Metabolism
- 2019 Analytical and Clinical Validation of Expressed Variants and Fusions From the Whole Transcriptome of Thyroid FNA Samples Frontiers in Endocrinology
- 2019 Analytical Verification Performance of Afirma Genomic Sequencing Classifier in the Diagnosis of Cytologically Indeterminate Thyroid Nodules Frontiers in Endocrinology
- 2019 Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms BMC Systems Biology
- 2018 Performance of a Genomic Sequencing Classifier for the Preoperative Diagnosis of Cytologically Indeterminate Thyroid Nodules JAMA Surgery
- 2016 The diagnostic application of RNA sequencing in patients with thyroid cancer: an analysis of 851 variants and 133 fusions in 524 genes BMC Bioinformatics
- 2012 Analytical Performance Verification of a Molecular Diagnostic for Cytology-Indeterminate Thyroid Nodules The Journal of Clinical Endocrinology & Metabolism
- 2012 Preoperative Diagnosis of Benign Thyroid Nodules with Indeterminate Cytology New England Journal of Medicine
- 2010 Molecular Classification of Thyroid Nodules Using High-Dimensionality Genomic Data The Journal of Clinical Endocrinology & Metabolism
Chapters
- Veracyte · CHAPTER 06 · APR 2008 – DEC 2022
- Afirma · CHAPTER 07 · JAN 2011 – JAN 2018
- Afirma GSC and the Xpression Atlas · CHAPTER 10 · MAY 2017 – SEP 2022
- A patent family · CHAPTER 11 · OCT 2019 – MAY 2025
Machine learning for clinical diagnostics
DEC 2010 – PRESENTThe method that links every classifier Kennedy has helped build since 2010: training algorithms on high-dimensional genomic data from clinical samples and validating them against histopathology. She presented on Veracyte's use of machine learning to translate genomic data into commercial diagnostic tests at the Precision Medicine World Conference in January 2018, and described the Afirma GSC's ensemble machine learning algorithms as deriving "from years of thoughtful scientific research, data analysis and statistical modeling". The same approach underlies the Envisia and Percepta classifiers and PinkDx's whole-transcriptome vaginal swab test.1815192021
- Genomic classifier development
- Analytical and clinical validation
- Ensemble algorithms
- Translating sequencing data into diagnostic tests
Organisations
- Veracyte, Inc. · SOUTH SAN FRANCISCO, CALIFORNIA
- PinkDx, Inc. · DALY CITY, CALIFORNIA
Technologies
- Ensemble machine learning classifiers · METHOD
The algorithmic approach behind Veracyte's sequencing-era classifiers and PinkDx's swab test. Kennedy said in 2017 that "the ensemble machine learning algorithms, which underlie the performance of Afirma GSC, derive from years of thoughtful scientific research, data analysis and statistical modeling", and that the company was "employing the same machine learning methods that are being used in other fields such as social media and self-driving cars". The 2019 BMC Systems Biology paper, with Kennedy as last author, describes a trio of machine learning algorithms for Hürthle cell nodules.
- Whole-transcriptome RNA sequencing · PLATFORM
The sequencing platform that replaced microarrays in Veracyte's second-generation tests. Kennedy described it at the 2018 Xpression Atlas launch: "Our RNA sequencing-based platform enables us to derive unprecedented amounts of rich genomic content from clinical samples." The Afirma GSC, Percepta GSC and Envisia classifiers are built on it, and PinkDx applies whole-transcriptome sequencing to vaginal swab samples in its endometrial cancer programme.
Publications
- 2026 Whole-transcriptome sequencing and machine learning detect molecular signatures of endometrial cancer in non-invasive vaginal swabs International Journal of Gynecological Cancer
- 2024 A Nasal Swab Classifier to Evaluate the Probability of Lung Cancer in Patients With Pulmonary Nodules Chest
- 2020 Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts BMC Medical Genomics
- 2019 Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms BMC Systems Biology
- 2018 Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions BMC Genomics
- 2018 Performance of a Genomic Sequencing Classifier for the Preoperative Diagnosis of Cytologically Indeterminate Thyroid Nodules JAMA Surgery
- 2017 Usual Interstitial Pneumonia Can Be Detected in Transbronchial Biopsies Using Machine Learning Annals of the American Thoracic Society
- 2015 Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data The Lancet Respiratory Medicine
- 2010 Molecular Classification of Thyroid Nodules Using High-Dimensionality Genomic Data The Journal of Clinical Endocrinology & Metabolism
Chapters
- Veracyte · CHAPTER 06 · APR 2008 – DEC 2022
- Afirma · CHAPTER 07 · JAN 2011 – JAN 2018
- Percepta and Envisia · CHAPTER 09 · APR 2015 – APR 2024
- Afirma GSC and the Xpression Atlas · CHAPTER 10 · MAY 2017 – SEP 2022
- A patent family · CHAPTER 11 · OCT 2019 – MAY 2025
- PinkDx · CHAPTER 13 · APR 2024 – PRESENT
- Reading endometrial cancer from a vaginal swab · CHAPTER 14 · JUL 2024 – PRESENT
Pulmonary genomic classifiers
APR 2015 – APR 2024Veracyte's second and third commercial tests took the thyroid approach to the lung. Percepta, launched April 16, 2015, classifies lung nodules that are inconclusive by bronchoscopy from bronchial brushings; Envisia, launched October 25, 2016, identifies the usual interstitial pneumonia pattern of idiopathic pulmonary fibrosis in transbronchial biopsies without surgical lung biopsy, and received Medicare coverage effective April 1, 2019. Kennedy is an author of the Envisia development and validation papers (Annals ATS 2017, BMC Genomics 2018, Lancet Respiratory Medicine 2019, AJRCCM 2021), the Percepta analytical and GSC papers, and the 2024 Chest validation of the Percepta Nasal Swab.2223242526274
- Lung nodules after inconclusive bronchoscopy
- Idiopathic pulmonary fibrosis diagnosis
- Usual interstitial pneumonia pattern
- Nasal swab lung cancer risk assessment
Organisations
- Veracyte, Inc. · SOUTH SAN FRANCISCO, CALIFORNIA
Technologies
- Percepta Bronchial Genomic Classifier · PRODUCT
Veracyte's lung cancer diagnostic, launched April 16, 2015, which classifies lung nodules and lesions that are inconclusive by bronchoscopy using bronchial brushing specimens. The next-generation Percepta Genomic Sequencing Classifier became available to physicians on June 26, 2019, and on May 19, 2021 Veracyte announced pivotal validation data for the Percepta Nasal Swab test for lung cancer risk, with Kennedy quoted as chief scientific officer and chief medical officer.
- Envisia Genomic Classifier · PRODUCT
Veracyte's classifier for idiopathic pulmonary fibrosis, launched at the CHEST Annual Meeting on October 25, 2016, where Kennedy presented clinical validity data. It identifies the usual interstitial pneumonia pattern in conventional transbronchial lung biopsy samples, offering an alternative to surgical lung biopsy; the prospective validation appeared in The Lancet Respiratory Medicine in 2019 and a study of the classifier as a complement to high-resolution CT in AJRCCM in 2021. Medicare coverage through the Palmetto GBA MolDX program took effect April 1, 2019.
- Whole-transcriptome RNA sequencing · PLATFORM
The sequencing platform that replaced microarrays in Veracyte's second-generation tests. Kennedy described it at the 2018 Xpression Atlas launch: "Our RNA sequencing-based platform enables us to derive unprecedented amounts of rich genomic content from clinical samples." The Afirma GSC, Percepta GSC and Envisia classifiers are built on it, and PinkDx applies whole-transcriptome sequencing to vaginal swab samples in its endometrial cancer programme.
- Ensemble machine learning classifiers · METHOD
The algorithmic approach behind Veracyte's sequencing-era classifiers and PinkDx's swab test. Kennedy said in 2017 that "the ensemble machine learning algorithms, which underlie the performance of Afirma GSC, derive from years of thoughtful scientific research, data analysis and statistical modeling", and that the company was "employing the same machine learning methods that are being used in other fields such as social media and self-driving cars". The 2019 BMC Systems Biology paper, with Kennedy as last author, describes a trio of machine learning algorithms for Hürthle cell nodules.
Publications
- 2024 A Nasal Swab Classifier to Evaluate the Probability of Lung Cancer in Patients With Pulmonary Nodules Chest
- 2021 Utility of a Molecular Classifier as a Complement to High-Resolution Computed Tomography to Identify Usual Interstitial Pneumonia American Journal of Respiratory and Critical Care Medicine
- 2020 Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts BMC Medical Genomics
- 2019 Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study The Lancet Respiratory Medicine
- 2018 Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions BMC Genomics
- 2017 Usual Interstitial Pneumonia Can Be Detected in Transbronchial Biopsies Using Machine Learning Annals of the American Thoracic Society
- 2016 Analytical performance of a bronchial genomic classifier BMC Cancer
- 2015 Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data The Lancet Respiratory Medicine
Chapters
- Veracyte · CHAPTER 06 · APR 2008 – DEC 2022
- Percepta and Envisia · CHAPTER 09 · APR 2015 – APR 2024
- A patent family · CHAPTER 11 · OCT 2019 – MAY 2025
Gynecologic cancer detection
2022 – PRESENTAt PinkDx, co-founded with Bonnie Anderson and launched publicly on April 25, 2024 with a $40 million Series A, Kennedy leads scientific strategy and translational research applying whole-transcriptome sequencing and machine learning to gynecologic cancer, starting with endometrial cancer. The exploratory PNK001 study enrolled 236 women undergoing hysterectomy in 2024 and showed that molecular signals of endometrial cancer can be detected from a vaginal swab (International Journal of Gynecological Cancer, April 2026); the PROACTION study (NCT06527157) is validating the test across 16 U.S. sites.28293031213233
- Endometrial cancer detection from vaginal swabs
- Less invasive diagnostics for abnormal uterine bleeding
- Gynecologic cancer diagnostics
Organisations
- PinkDx, Inc. · DALY CITY, CALIFORNIA
Technologies
- PinkDx vaginal swab classifier for endometrial cancer · ASSAY
PinkDx's first product in development: a clinician-collected vaginal swab, with no speculum required, for endometrial cancer in women with abnormal bleeding. The sample is shipped to the PinkDx laboratory in California and an algorithm classifies it as positive or not positive for endometrial cancer. The exploratory PNK001 study (NCT06460818) showed that molecular signals of endometrial cancer can be read from a vaginal swab by whole-transcriptome sequencing and machine learning (IJGC, 2026), and the PROACTION study (NCT06527157) is validating the test.
- Whole-transcriptome RNA sequencing · PLATFORM
The sequencing platform that replaced microarrays in Veracyte's second-generation tests. Kennedy described it at the 2018 Xpression Atlas launch: "Our RNA sequencing-based platform enables us to derive unprecedented amounts of rich genomic content from clinical samples." The Afirma GSC, Percepta GSC and Envisia classifiers are built on it, and PinkDx applies whole-transcriptome sequencing to vaginal swab samples in its endometrial cancer programme.
- Ensemble machine learning classifiers · METHOD
The algorithmic approach behind Veracyte's sequencing-era classifiers and PinkDx's swab test. Kennedy said in 2017 that "the ensemble machine learning algorithms, which underlie the performance of Afirma GSC, derive from years of thoughtful scientific research, data analysis and statistical modeling", and that the company was "employing the same machine learning methods that are being used in other fields such as social media and self-driving cars". The 2019 BMC Systems Biology paper, with Kennedy as last author, describes a trio of machine learning algorithms for Hürthle cell nodules.
Publications
- 2026 Whole-transcriptome sequencing and machine learning detect molecular signatures of endometrial cancer in non-invasive vaginal swabs International Journal of Gynecological Cancer
Chapters
- PinkDx · CHAPTER 13 · APR 2024 – PRESENT
- Reading endometrial cancer from a vaginal swab · CHAPTER 14 · JUL 2024 – PRESENT