{"id":46396,"date":"2022-07-20T20:01:51","date_gmt":"2022-07-20T18:01:51","guid":{"rendered":"https:\/\/pharma-trend.com\/en\/tobias-kind-leader-in-computational-metabolomics-joins-enveda-biosciences\/"},"modified":"2022-07-20T20:01:51","modified_gmt":"2022-07-20T18:01:51","slug":"tobias-kind-leader-in-computational-metabolomics-joins-enveda-biosciences","status":"publish","type":"post","link":"https:\/\/pharma-trend.com\/en\/tobias-kind-leader-in-computational-metabolomics-joins-enveda-biosciences\/","title":{"rendered":"Tobias Kind, Leader in Computational Metabolomics, Joins Enveda Biosciences"},"content":{"rendered":"
\n

BOULDER, Colo.–(BUSINESS WIRE)–Enveda Biosciences, a pioneer in small molecule drug discovery using machine learning and metabolomics to harness the potential of natural products, today announced that Tobias Kind, Ph.D., will join the company\u2019s industry-leading data science team as Research Fellow. Dr. Kind is one of the world\u2019s most respected and highly cited researchers in computational metabolomics and natural products research. He will play a key role in driving continued data science innovation for Enveda\u2019s drug discovery platform and the company\u2019s leadership in metabolomics.\n<\/p>\n

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\nDr. Kind brings more than 25 years of experience to Enveda through his transforming work in the use of mass spectrometry (MS) for the structural elucidation of small molecules through machine learning, quantum chemistry and other technologies. He also is widely noted for his articulation of the \u201cSeven Golden Rules,\u201d the use of in silico MS\/MS databases and the use of retention time prediction with mass spectrometry, all of which improve biological interpretations of metabolomics data.\n<\/p>\n

\n\u201cDr. Kind has extraordinary expertise, particularly with the application of new technologies to the structural elucidation of small molecules, including natural products like those we are targeting,\u201d said Viswa Colluru, Ph.D., Enveda\u2019s CEO. \u201cWe are excited to bring together Dr. Kind\u2019s strong record of producing significant innovations and the advances that Enveda\u2019s team already has achieved. Dr. Kind will play an important role in our efforts to continue to build a discovery platform that is even more powerful, precise and efficient.\u201d\n<\/p>\n

\nBefore joining Enveda, Dr. Kind was a team leader and senior researcher at the University of California, Davis. His research focused on identifying the structures of small molecules with mass spectrometry, predicting in silico mass spectra with quantum chemistry, and using machine learning for mass spectral predictions and small molecule identifications.\n<\/p>\n

\n\u201cIt\u2019s a privilege to be a part of Enveda\u2019s team,\u201d Dr. Kind said. \u201cEven before I joined Enveda, I was impressed with the company, its leadership and the caliber of the data science team. I have been particularly struck by their innovative advances in spectral inference, an interest of mine, which give Enveda\u2019s process significant advantages. I am looking forward to working with my new colleagues to identify new ways to make Enveda\u2019s platform even more powerful.\u201d\n<\/p>\n

\nPrior to his nearly two decades at UC Davis, Dr Kind was a postdoctoral fellow at Max-Planck-Institute of Molecular Plant Physiology, Golm, Germany, one of the world\u2019s most prestigious research institutions. He was affiliated with the UFZ-Environmental Research Centre Leipzig-Halle\u2019s Department of Chemical Ecotoxicology prior to his time at the Max Planck Society. He earned his Ph.D. and M.S., both in analytical chemistry, from the University of Leipzig, Germany.\n<\/p>\n

\nAbout Enveda Biosciences<\/b>\n<\/p>\n

\nEnveda Biosciences is a biotechnology company building the first high-resolution chemical map of the natural world to tackle the toughest problems in drug discovery. Enveda\u2019s platform is the world\u2019s most advanced drug discovery search engine for the almost limitless expanse of nature\u2019s unknown chemistry, building on years of cutting-edge advancements at the intersection of metabolomics and machine learning. Complementing its breakthrough technology, Enveda\u2019s team includes seasoned drug hunters with decades of experience in the pharmaceutical industry working alongside world-leading data scientists. For more information on Enveda, visit envedabio.com<\/a>.\n<\/p>\n

Contacts<\/b> <\/p>\n

\nRod Hise
\n
Director, Corporate Communications
\n
608-770-7850
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rod.hise@envedabio.com<\/a>\n<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

BOULDER, Colo.–(BUSINESS WIRE)–Enveda Biosciences, a pioneer in small molecule drug discovery using machine learning and metabolomics to harness the potential of natural products, today announced that Tobias Kind, Ph.D., will join the company\u2019s industry-leading data science team as Research Fellow. Dr. Kind is one of the world\u2019s most respected and highly cited researchers in computational … [Read more…]<\/a><\/span><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-business","4":"post-46396","6":"format-standard","7":"category-industry"},"yoast_head":"\nTobias Kind, Leader in Computational Metabolomics, Joins Enveda Biosciences - Pharma Trend<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pharma-trend.com\/en\/tobias-kind-leader-in-computational-metabolomics-joins-enveda-biosciences\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Tobias Kind, Leader in Computational Metabolomics, Joins Enveda Biosciences - Pharma Trend\" \/>\n<meta property=\"og:description\" content=\"BOULDER, Colo.–(BUSINESS WIRE)–Enveda Biosciences, a pioneer in small molecule drug discovery using machine learning and metabolomics to harness the potential of natural products, today announced that Tobias Kind, Ph.D., will join the company\u2019s industry-leading data science team as Research Fellow. 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