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
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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
The Resonance Test 97: The Power of Partnership with Colleen Kapase and Elaina Shekhter
The EPAM Continuum Podcast Network
35 minutes 17 seconds
4 months ago
The Resonance Test 97: The Power of Partnership with Colleen Kapase and Elaina Shekhter
In the age of AI, there’s no going it alone. Partnership is now an absolute necessity.
This conversation between Colleen Kapase, VP of Channels and Partner Programs at Google Cloud, and Elaina Shekhter, EPAM’s Chief Marketing and Strategy Officer, demonstrates the value of partnership done right. Their back-and-forth embodies the enduring partnership, and unshakable trust, that Goole Cloud and EPAM have built over the years.
Kapase notes that the conversations she's had with partners were often about modernizing cloud infrastructure rather than more nuanced AI discussions. No more! “It's moved beyond a CIO conversation to a product conversation, to a CMO conversation.” Google and their partners are asking: “What are you doing to leverage AI to advance our products or offerings or processes and customer experience?”
This kind of working is, Kapase says, an opportunity to “grow, grow, grow, grow” that can deeply impact their partners’ customer experience and product development.
Shekhter says that lately there has been much restructuring of the partner ecosystem and then asks bluntly: What is partnership *for?*
“Just delighting the customer,” says Kapase. “I don't know if it gets any more complicated than that.”
Complicating things somewhat, Shekhter wonders if her interlocutor has advice on how partnership can be customer-centric in AI-native transformation work.
“It can sound basic, but communication is *so* important,” says Kapase. “It is really the basis of any great partnership… Strong communication just can make you better together.”
Better together, indeed.
So, for those who are in or want to join the Google Cloud crowd, or care about partnerships more generally, listen up! Much here to learn about partner-driven delivery and adoption, the role of Agentspace and AI innovation, the importance of optimism, and more.
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
