
Sign up to save your podcasts
Or
This week, we’re delighted to be joined by Cody Schiffer, Associate Director, Machine Learning at SMPA - a biopharmaceutical company focused on delivering therapeutic and scientific breakthroughs in areas of critical patient need,
During this conversation, Cody and Ross discuss the construction, maintenance, and application of a knowledge graphic in biopharma, including how to integrate structured and unstructured data to support tasks like literature searches, competitive intelligence and drug discovery and the challenges in keeping a knowledge graph updated with new, real-time information.
Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in life sciences.
Discussed:
[1:09] Cody shares his background and career to date.
[2:43] Cody outlines how SMPA leverages data science to support its pipeline of investigational assets in healthcare.
[7:36] Cody explains how his team approaches helping scientists better understand scientific literature.
[12:44] Cody explains how the SMPA knowledge graph was constructed and how it is updated over time.
[18:13] Cody discusses how his team incorporates unstructured data in the knowledge graph.
[23:05] Cody explains how they apply weighting to the information that is gathered and ultimately fed into the knowledge graph.
[28:16] Cody shares the biggest lessons he has learned from building and maintaining the knowledge graph.
[34:48] Cody explains how he and SMPA view the build versus buy question when developing internal tools.
[38:47] Cody shares his thoughts on what the future holds for his team and the tools they are building internally.
---
If you’re a biotech company struggling to unlock a data challenge, CorrDyn can help.
Whether you need to supplement existing technology teams with specialist expertise or launch a data program that lays the groundwork for future internal hires, you can partner with Corrdyn to unlock the potential of your business data - today.
Visit connect.corrdyn.com/biotech to learn more.
5
1010 ratings
This week, we’re delighted to be joined by Cody Schiffer, Associate Director, Machine Learning at SMPA - a biopharmaceutical company focused on delivering therapeutic and scientific breakthroughs in areas of critical patient need,
During this conversation, Cody and Ross discuss the construction, maintenance, and application of a knowledge graphic in biopharma, including how to integrate structured and unstructured data to support tasks like literature searches, competitive intelligence and drug discovery and the challenges in keeping a knowledge graph updated with new, real-time information.
Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in life sciences.
Discussed:
[1:09] Cody shares his background and career to date.
[2:43] Cody outlines how SMPA leverages data science to support its pipeline of investigational assets in healthcare.
[7:36] Cody explains how his team approaches helping scientists better understand scientific literature.
[12:44] Cody explains how the SMPA knowledge graph was constructed and how it is updated over time.
[18:13] Cody discusses how his team incorporates unstructured data in the knowledge graph.
[23:05] Cody explains how they apply weighting to the information that is gathered and ultimately fed into the knowledge graph.
[28:16] Cody shares the biggest lessons he has learned from building and maintaining the knowledge graph.
[34:48] Cody explains how he and SMPA view the build versus buy question when developing internal tools.
[38:47] Cody shares his thoughts on what the future holds for his team and the tools they are building internally.
---
If you’re a biotech company struggling to unlock a data challenge, CorrDyn can help.
Whether you need to supplement existing technology teams with specialist expertise or launch a data program that lays the groundwork for future internal hires, you can partner with Corrdyn to unlock the potential of your business data - today.
Visit connect.corrdyn.com/biotech to learn more.
37,849 Listeners
30,668 Listeners
32,107 Listeners
1,856 Listeners
9,250 Listeners
1,451 Listeners
122 Listeners
9,500 Listeners
316 Listeners
188 Listeners
88 Listeners
30 Listeners
144 Listeners
15,397 Listeners
18 Listeners