Ravi Radhakrishnan: Difference between revisions

'''Ravi Radhakrishnan''' is an [[American]] [[engineer]] and an [[academic]]. He is the [[Herman P. Schwan]] Chair of Bioengineering as well as a professor in the Department of Chemical and Biomolecular Engineering at the [[University of Pennsylvania]].<ref name=es>{{citeCite web|url=https://directory.seas.upenn.edu/ravi-radhakrishnan/|title=Ravi Radhakrishnan - Penn Engineering}}</ref>

Radhakrishnan's work is centered around creating digital models for [[biomedical engineering]] applications, particularly in [[cancer]] treatment and [[nanomedicine]]. His work has also focused on computational algorithms across molecular and cellular scales, using [[machine learning]], [[Artificial intelligence|AI]], [[Statistical mechanics|statistical mechanics]], and high-performance scientific computing on parallel architectures. His works have been published in academic journals, including ''[[Journal of Physics: Condensed Matter]]'' and ''[[Nature]]''.<ref>{{citeCite web|url=https://scholar.google.com/citations?user=izxlpPwAAAAJ&hl=en|title=Raviravi Radhakrishnan - Google Scholarradhakrishnan|website=scholar.google.com}}</ref>

Radhakrishnan completed his [[Bachelor of Technology|B.Tech]] in [[Chemical Engineering]] from the [[Indian Institute of Technology]] in 1995. He later obtained his [[PHD|Ph.D.]] in Chemical Engineering from [[Cornell University]] in 2001.<ref>{{citeCite web|url=https://cbe.seas.upenn.edu/faculty/ravi-radhakrishnan/|title=Ravi Radhakrishnan - Penn Engineering}}</ref>

Radhakrishnan's research interests include nanobiotechnology, molecular systems biology, statistical mechanics, multiscale modeling, insilico oncology and systems pharmacology. Investigating phase separation and phase equilibria in porous materials, his 1999 study highlighted a solid understanding of pure adsorbates in simple geometries, and called for advanced models to address complex geometries, chemical and geometrical heterogeneity, and the largely unexplored phase separation in mixtures.<ref>{{cite web|url=https://iopscience.iop.org/article/10.1088/0034-4885/62/12/201|title=Phase separation in confined systems}}</ref> In 2004, he co-authored a paper with T Schlick. The paper used transition path sampling to uncover the atomic and energetic details of the conformational changes in DNA polymerase β that precede nucleotide incorporation, identified key residues and cooperative dynamics crucial for the enzyme's function and fidelity, and provided a protocol applicable to other biomolecular reactions.<ref>{{citeCite webjournal|url=https://www.pnas.org/doi/full/10.1073/pnas.0308585101|title=Orchestration of cooperative events in DNA synthesis and repair mechanism unraveled by transition path sampling of DNA polymerase β's closing|first1=Ravi|last1=Radhakrishnan|first2=Tamar|last2=Schlick|date=April 20, 2004|journal=Proceedings of the National Academy of Sciences|volume=101|issue=16|pages=5970–5975|via=CrossRef|doi=10.1073/pnas.0308585101|pmid=15069184|pmc=PMC395907}}</ref> His 2006 collaborative study with C Alba-Simionesco investigated how confinement within various porous materials influenced the freezing, melting, and structural properties of adsorbates, highlighting new surface-driven and confinement-driven phases, as well as the effects on the glass transition.<ref>{{cite web|url=https://iopscience.iop.org/article/10.1088/0953-8984/18/6/R01|title=Effects of confinement on freezing and melting}}</ref>

Radhakrishnan's 2010 paper investigated ErbB3/HER3 kinase activity, revealing its capacity for autophosphorylation and ATP binding despite structural differences, suggesting its role in signaling pathways and its potential as a therapeutic target in cancer.<ref>{{citeCite webjournal|url=https://pubmed.ncbi.nlm.nih.gov/20351256/|title=ErbB3/HER3 intracellular domain is competent to bind ATP and catalyze autophosphorylation|first1=Fumin|last1=Shi|first2=Shannon E.|last2=Telesco|first3=Yingting|last3=Liu|first4=Ravi|last4=Radhakrishnan|first5=Mark A.|last5=Lemmon|date=April 27, 2010|journal=Proceedings of the National Academy of Sciences of the United States of America|volume=107|issue=17|pages=7692–7697|via=PubMed|doi=10.1073/pnas.1002753107|pmid=20351256|pmc=2867849}}</ref> Later, his 2014 study investigated the prevalence, prognostic significance, and therapeutic implications of ALK mutations in neuroblastoma, highlighting their association with poorer survival and potential for personalized treatment strategies based on mutation profiles.<ref>{{citeCite webjournal|url=https://pubmed.ncbi.nlm.nih.gov/25517749/|title=ALK mutations confer differential oncogenic activation and sensitivity to ALK inhibition therapy in neuroblastoma|first1=Scott C.|last1=Bresler|first2=Daniel A.|last2=Weiser|first3=Peter J.|last3=Huwe|first4=Jin H.|last4=Park|first5=Kateryna|last5=Krytska|first6=Hannah|last6=Ryles|first7=Marci|last7=Laudenslager|first8=Eric F.|last8=Rappaport|first9=Andrew C.|last9=Wood|first10=Patrick W.|last10=McGrady|first11=Michael D.|last11=Hogarty|first12=Wendy B.|last12=London|first13=Ravi|last13=Radhakrishnan|first14=Mark A.|last14=Lemmon|first15=Yaël P.|last15=Mossé|date=November 10, 2014|journal=Cancer Cell|volume=26|issue=5|pages=682–694|via=PubMed|doi=10.1016/j.ccell.2014.09.019|pmid=25517749|pmc=4269829}}</ref> Moreover, in 2018, he analyzed how metastatic melanomas utilized exosomal PD-L1, influenced by IFN-γ, to suppress CD8 T cell function, correlating levels with patient response to anti-PD-1 therapy and suggesting exosomal PD-L1 as a potential biomarker.<ref>{{citeCite webjournal|url=https://www.nature.com/articles/s41586-018-0392-8|title=Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response|first1=Gang|last1=Chen|first2=Alexander C.|last2=Huang|first3=Wei|last3=Zhang|first4=Gao|last4=Zhang|first5=Min|last5=Wu|first6=Wei|last6=Xu|first7=Zili|last7=Yu|first8=Jiegang|last8=Yang|first9=Beike|last9=Wang|first10=Honghong|last10=Sun|first11=Houfu|last11=Xia|first12=Qiwen|last12=Man|first13=Wenqun|last13=Zhong|first14=Leonardo F.|last14=Antelo|first15=Bin|last15=Wu|first16=Xuepeng|last16=Xiong|first17=Xiaoming|last17=Liu|first18=Lei|last18=Guan|first19=Ting|last19=Li|first20=Shujing|last20=Liu|first21=Ruifeng|last21=Yang|first22=Youtao|last22=Lu|first23=Liyun|last23=Dong|first24=Suzanne|last24=McGettigan|first25=Rajasekharan|last25=Somasundaram|first26=Ravi|last26=Radhakrishnan|first27=Gordon|last27=Mills|first28=Yiling|last28=Lu|first29=Junhyong|last29=Kim|first30=Youhai H.|last30=Chen|first31=Haidong|last31=Dong|first32=Yifang|last32=Zhao|first33=Giorgos C.|last33=Karakousis|first34=Tara C.|last34=Mitchell|first35=Lynn M.|last35=Schuchter|first36=Meenhard|last36=Herlyn|first37=E. John|last37=Wherry|first38=Xiaowei|last38=Xu|first39=Wei|last39=Guo|date=August 3, 2018|journal=Nature|volume=560|issue=7718|pages=382–386|via=www.nature.com|doi=10.1038/s41586-018-0392-8}}</ref> In 2023, he explored how extracellular matrix stiffness promoted tumor progression by stimulating exosome secretion from cancer cells via an Akt-Rab8 pathway, and demonstrated that exosomes derived under these conditions enhanced tumor growth and activated Notch signaling in recipient cells, indicating a pivotal role for mechanical cues in regulating the tumor microenvironment.<ref>{{citeCite webjournal|url=https://www.nature.com/articles/s41556-023-01092-1|title=Stiff matrix induces exosome secretion to promote tumour growth|first1=Bin|last1=Wu|first2=Di-Ao|last2=Liu|first3=Lei|last3=Guan|first4=Phyoe Kyawe|last4=Myint|first5=LiKang|last5=Chin|first6=Hien|last6=Dang|first7=Ye|last7=Xu|first8=Jinqi|last8=Ren|first9=Ting|last9=Li|first10=Ziyan|last10=Yu|first11=Sophie|last11=Jabban|first12=Gordon B.|last12=Mills|first13=Jonathan|last13=Nukpezah|first14=Youhai H.|last14=Chen|first15=Emma E.|last15=Furth|first16=Phyllis A.|last16=Gimotty|first17=Rebecca G.|last17=Wells|first18=Valerie M.|last18=Weaver|first19=Ravi|last19=Radhakrishnan|first20=Xin Wei|last20=Wang|first21=Wei|last21=Guo|date=March 3, 2023|journal=Nature Cell Biology|volume=25|issue=3|pages=415–424|via=www.nature.com|doi=10.1038/s41556-023-01092-1}}</ref>

*2015 – Fellow, [[American Institute for Medical and Biological Engineering]]<ref>{{citeCite web|url=https://aimbe.org/college-of-fellows/cof-1858/|title=AIMBERavi CollegeRadhakrishnan, ofPh.D. FellowsCOF-1858 Class- of 2015AIMBE}}</ref>

*2022 – Fellow, [[Biomedical Engineering Society]]<ref>{{citeCite web|url=https://www.bmes.org/news/2022awardwinners|title=Announcing the 2022 Award Winnerswinners and Classclass of Fellows - Biomedical Engineering Society|website=www.bmes.org}}</ref>