Home
Categories
EXPLORE
True Crime
Comedy
Society & Culture
Business
Sports
History
Music
About Us
Contact Us
Copyright
© 2024 PodJoint
00:00 / 00:00
Sign in

or

Don't have an account?
Sign up
Forgot password
https://is1-ssl.mzstatic.com/image/thumb/Podcasts71/v4/ec/3c/ac/ec3cac17-d460-db87-1f08-e7b2ff1a02ff/mza_2395170188661892592.jpg/600x600bb.jpg
The EPAM Continuum Podcast Network
EPAM Continuum
174 episodes
3 weeks ago
When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI. This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data & AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era. “We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics. Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.” Which means, for pharma, much uncertainty and much experimentation. “I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.” Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.” Will AI make the big difference, finally? “Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.” Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.” Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’” Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!). In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.” Host: Alison Kotin Engineer: Kyp Pilalas Producer: Ken Gordon
Show more...
Business
RSS
All content for The EPAM Continuum Podcast Network is the property of EPAM Continuum and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI. This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data & AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era. “We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics. Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.” Which means, for pharma, much uncertainty and much experimentation. “I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.” Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.” Will AI make the big difference, finally? “Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.” Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.” Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’” Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!). In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.” Host: Alison Kotin Engineer: Kyp Pilalas Producer: Ken Gordon
Show more...
Business
https://i1.sndcdn.com/artworks-CCB1jWJ0IBjvtjub-uzezvw-t3000x3000.png
The Resonance Test 96: Building an Aquatic Corporate Community with Antonio Silva & Kate Pretkel
The EPAM Continuum Podcast Network
26 minutes 24 seconds
7 months ago
The Resonance Test 96: Building an Aquatic Corporate Community with Antonio Silva & Kate Pretkel
What does the phrase “aquatic corporate community” mean to you? A school of fish in business suits holding an underwater meeting around a table of coral? Well, for our guests on the latest episode of *The Resonance Test,* it’s all about plunging into a strategic social responsibility program called “Let’s Swim Together.” Antonio Silva, President of European Aquatics, and Kate Pretkel, EPAM’s VP and Head of Sustainability Programs, have pooled their knowledge to answer questions from Balázs Magyar, Senior Director of Account Management at EPAM. Swimming is not just sports skill, says Silva, “It's a life skill.” He rightly points out that the pool is a place that can be used by everyone: babies, children, and adults. And, as Magyar notes, it promotes discipline, responsibility, social connections, and physical- and mental health. “Let’s Swim Together,” is starting with a pilot program for EPAM Hungary but the program will expand to other companies, other countries. Silva adds that with this initiative, we can reach “the specific goals of a company” and “so-called environmental, social and governance goals.” This is good news for Pretkel, who speaks ESG fluently. She says that EPAM has a long tradition of helping employees “to make a good impact on the communities that we live and work in,” adding that “It's not *just* about people working for a specific company, but also their friends, their families, their kids and their communities.” The challenge, with all these groups, is getting people to take the first step toward the water. “We are looking at the whole employee experience,” says Pretkel. The trick is making it easier for our employees to join. To do so, they are incorporated into the “overall experience that we are creating for them.” She says it’s all about “building these habits and also in some cases engaging the team so they can help each other to make this first step.” In short, Silva and Pretkel are excited about building what Antonio calls, yes, “the aquatic corporate community.” He concludes: “It's about reaching some social goals that [the participants] could not reach if they were not involved in such an activity.” Host: Macy Donaway Engineer: Kyp Pilalas Producer: Ken Gordon
The EPAM Continuum Podcast Network
When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI. This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data & AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era. “We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics. Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.” Which means, for pharma, much uncertainty and much experimentation. “I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.” Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.” Will AI make the big difference, finally? “Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.” Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.” Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’” Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!). In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.” Host: Alison Kotin Engineer: Kyp Pilalas Producer: Ken Gordon