About

Professor Peter Kim is a researcher in the Department of Biochemistry at Stanford University. His lab combines structural biology, protein engineering, immunology, and machine learning to advance global health, with a focus on creating vaccines and developing new strategies to enable vaccine generation. Notably, he received an $18 million grant to develop broadly effective antiviral vaccines targeting viruses such as Ebola and Marburg, including those that have yet to emerge. His work aims to address critical challenges in vaccine development and contribute to global health security.

Research topics

• Computer Science
• Biology
• Cancer research
• Immunology
• Bioinformatics
• Medicine
• Ecology
• Engineering
• Oncology
• Biochemical engineering
• Internal medicine
• Environmental science
• Chemistry
• Intensive care medicine

Selected publications

• Specialized Plant Growth Chamber Designs to Study Complex Rhizosphere Interactions

  Frontiers in Microbiology · 2021 · 48 citations

  • Computer Science
  • Biology
  • Ecology

  study of rhizosphere interactions, specialized plant growth chamber systems have been developed that mimic the natural growth environment. This review discusses the currently available lab-based systems ranging from widely known rhizotrons to other emerging devices designed to allow continuous monitoring and non-destructive sampling of the rhizosphere ecosystems in real-time throughout the developmental stages of a plant. We categorize them based on the major rhizosphere processes it addresses and identify their unique challenges as well as advantages. We find that while some design elements are shared among different systems (e.g., size exclusion membranes), most of the systems are bespoke and speaks to the intricacies and specialization involved in unraveling the details of rhizosphere processes. We also discuss what we describe as the next generation of growth chamber employing the latest technology as well as the current barriers they face. We conclude with a perspective on the current knowledge gaps in the rhizosphere which can be filled by innovative chamber designs.

  DOI

• Biomarkers for hepatocellular cancer

  World Journal of Hepatology · 2020 · 39 citations

  • Medicine
  • Internal medicine
  • Intensive care medicine

  Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. If diagnosed early, curative treatment options such as surgical resection, loco-regional therapies, and liver transplantation are available to patients, increasing their chances of survival and improving their quality of life. Unfortunately, most patients are diagnosed with late stage HCC where only palliative treatment is available. Therefore, biomarkers which could detect HCC early with a high degree of sensitivity and specificity, may play a crucial role in the diagnosis and management of the disease. This review will aim to provide an overview of the different biomarkers of HCC comprising those used in the diagnosis of HCC in at risk populations, as well as others with potential for prognosis, risk predisposition and prediction of response to therapeutic intervention.

  DOI

• Optimising Hydrogel Release Profiles for Viro-Immunotherapy Using Oncolytic Adenovirus Expressing IL-12 and GM-CSF with Immature Dendritic Cells

  Applied Sciences · 2020 · 24 citations

  Senior authorCorresponding
  • Cancer research
  • Biology
  • Immunology

  Sustained-release delivery systems, such as hydrogels, significantly improve cancer therapies by extending the treatment efficacy and avoiding excess wash-out. Combined virotherapy and immunotherapy (viro-immunotherapy) is naturally improved by these sustained-release systems, as it relies on the continual stimulation of the antitumour immune response. In this article, we consider a previously developed viro-immunotherapy treatment where oncolytic viruses that are genetically engineered to infect and lyse cancer cells are loaded onto hydrogels with immature dendritic cells (DCs). The time-dependent release of virus and immune cells results in a prolonged cancer cell killing from both the virus and activated immune cells. Although effective, a major challenge is optimising the release profile of the virus and immature DCs from the gel so as to obtain a minimum tumour size. Using a system of ordinary differential equations calibrated to experimental results, we undertake a novel numerical investigation of different gel-release profiles to determine the optimal release profile for this viro-immunotherapy. Using a data-calibrated mathematical model, we show that if the virus is released rapidly within the first few days and the DCs are released for two weeks, the tumour burden can be significantly decreased. We then find the true optimal gel-release kinetics using a genetic algorithm and suggest that complex profiles present unnecessary risk and that a simple linear-release model is optimal. In this work, insight is provided into a fundamental problem in the growing field of sustained-delivery systems using mathematical modelling and analysis.

  DOI

Recent grants

• NIH Grant R01GM044162

  NIH · $2.8M · 2003

Frequent coauthors

• Sonia N. Yeung

  University of British Columbia

  44 shared

• Alejandro Lichtinger

  43 shared

• David S. Rootman

  University of Toronto

  39 shared

• Peter P. Lee

  31 shared

• David F. Grabski

  University of Virginia

  29 shared

• Soumitra Saha

  Chandigarh University

  29 shared

• Scott Corlew

  Harvard University

  29 shared

• Etienne St‐Louis

  Montreal Children's Hospital

  29 shared

Labs

• the Peter Kim LabPI

Similar researchers at Stanford University

• Yi Cuih-287
• Zhenan Baoh-224
• Karl Deisserothh-218
• Michael Snyderh-215
• Roger Blandfordh-205