Navigating the future of product development

Cornell Tech networking event

Keeping pace with the swift disruption of artificial intelligence (AI) and other trends in tech has proven to be a challenge across industries. Cornell Tech product and technology experts Keith Cowing and Josh Hartmann know firsthand how emerging technologies and attitude shifts can prompt radical changes in the world of product development.

The Product and Tech Leadership Summit, which will take place this September at Cornell Tech in New York City, is an immersive learning and networking experience for professionals who lead product teams. They will learn from industry leaders, AI researchers and expert Cornell faculty how to leverage transformation techniques to build high-performing products and tech teams. Cowing and Hartmann recently shared a preview of the Summit’s topics:

Use Available Tools and Understand New Opportunities

While the rapid pace of change in the product development space can feel overwhelming, Cowing and Hartmann suggest using existing tools rather than shying away from them. According to Hartmann, it is unlikely that ChatGPT represents the full reality of the AI-integrated future, but professionals should be familiar with it and other current tools. Familiarity can empower executives to create plans of action: “You can’t shift the entire enterprise all at once, but what are the pieces of the enterprise that you can start to move over?” asked Hartmann, chief practice officer for Cornell Tech.

Hartmann and Cowing agree that companies must continue the work to understand and harness the power of AI. Generative AI can perform data analysis and write code, potentially allowing the automation of complex processes such as optimizing web pages for mobile.

“Some companies are building as their product – they’re AI companies. Some will put AI in their product and augment what they do. And then some will just be more efficient with it, and that’s going to affect everybody,” said Cowing, a visiting lecturer at Cornell Tech.

Breakthroughs in spatial computing technology, led by Apple’s recently announced Vision Pro, also present a range of critical product development opportunities and obstacles. “It’s too early to know if the vision – pun intended – is going to stand up. If it does, then we’re also going to see major reskilling required in our teams,” Hartmann said.

Focus on the Customer

A shift toward customer-focused strategy is driving change in the product development industry. Airbnb, for example, has made sweeping changes to its product with the intent of improving the customer experience. For Cowing and Hartmann, AI carries the potential to accelerate such processes.

How do we implement AI and build a tooling around it that will help our customers get the job done? And that’s the key … the sweet spot comes when you can integrate AI and build value and context around AI on behalf of your customer. You can use and apply your deep understanding of your customers’ needs and use AI as an accelerant, a force multiplier,” Hartmann said.

Make a Positive Impact

While recent advancements in AI and spatial computing create many new possibilities, they also prompt serious ethical questions. Hartmann and Cowing contend that the difference that these technologies create in the world will depend on the people who implement them.

“Somehow [we must create] the incentives in the system so that people want to do the right thing and are encouraged to do the right thing,” said Cowing.

To influence positive change through new tech, Hartmann encourages professionals to pursue careers with mission-driven companies and leaders: “Be intentional about where you work. It really does come from the top,” he said.

Cowing and Hartmann look forward to welcoming professionals to the apply early.

Want to learn more before applying?

 

This story was drafted by eCornell marketing intern Justin Heitzman.

Generative AI for Business Transformation certificate empowers leaders to improve productivity

Finger touching a screen and creating a sparkling effect against a blue background

As artificial intelligence (AI) continues to reshape industries, Cornell Tech and the SC Johnson College of Business have partnered to launch Generative AI for Business Transformation, a new, live online certificate program to equip professionals with the knowledge and skills needed to harness the power of AI.

“Organizations and individuals who can harness the potential of AI will gain a huge advantage, while those taken by the hype who don’t upskill and prepare will risk obsolescence,” said Karan Girotra, faculty author, Cornell Tech professor and Charles H. Dyson Family Professor of Management. “This certificate program is designed to provide participants with a deep understanding of the capabilities and compromises of AI, and empower them with skills to increase their managerial effectiveness and transform business processes.”

Recent advances in AI have enabled machines to outperform humans in several kinds of knowledge work, particularly in producing linguistic and visual elements based on large volumes of information. Girotra emphasizes the remarkable potential of the underlying technologies, which are facilitating breakthroughs in medicine, chemistry and physics.

The live online certificate program available through eCornell, will span five weeks, beginning April 29, 2024, and will be conducted by Girotra on Mondays and Wednesdays from 5 p.m. to 7:30 p.m. ET. Participants will evaluate the most effective ways to adopt AI technologies, exploring how AI enables new, automated, highly scalable and low-cost methods of cognitive work. The curriculum will also address AI’s ethical and legal concerns, underscoring the need for responsible adoption and policymaking.

Girotra notes that while AI offers immense opportunities, it also presents challenges: “These new capabilities also empower bad actors, open new ethical and legal concerns and test regulatory frameworks. There is also a significant probability of a monopoly provider of the technology. This could shift economic power to Big Tech, posing a long-term existential threat to smaller organizations engaged in work that can be automated. This program will help participants navigate these complexities and leverage AI responsibly.”

The Generative AI for Business Transformation certificate is positioned as a crucial resource for leaders looking to stay ahead in an increasingly AI-driven world. Organizations and individuals seeking to transform their businesses or careers are encouraged to explore this innovative offering from eCornell. The certificate will be delivered live and space in the program is limited. Learn more and enroll.

Supply chain management meets modern analytics in Cornell certificate program

While supply chain disruptions caused by the COVID-19 pandemic have mostly eased, predicting customer demand and other elements of supply chain management continue to present companies with complex existential challenges.

The crisis laid bare the vulnerabilities in traditional forecasting models – where a single miscalculation could lead to product shortages and severe revenue losses – and revealed the need for a more advanced data-driven approach.

The eight-week Supply Chain Analytics online certificate program from the Cornell SC Johnson Graduate School of Management equips specialists from various sectors with strategies to master key elements of supply chain management. Li Chen, professor of operations, technology and information management, leads the program.

“We know that the future is unpredictable, right? But we still want to make predictions. The idea is to look at historical sales and demand data, and based on that, utilize formulas to make good demand forecasts,” Chen said. “I teach this data-driven approach with a focus on measuring forecast performance as well. Every time you forecast, you should compare it to the actuals to gauge the accuracy of your predictions, so you can refine your methods over time.”

Diving into topics like demand variability and inventory management, the program provides a robust set of tools for actionable insights. It digs into inevitable trade-offs between reducing inventory and increasing transportation costs, offering a nuanced perspective to students interested in supply chain consulting and analyst roles or anyone who seeks to better understand the strategic aspect of operations management and logistics.

The instruction provided on industry standard operations and inventory management systems also highlights underutilized functionalities of software designed to improve the efficiency of supply chain configurations.

“This content will truly help people, especially those using systems like SAP or Oracle, to appreciate what’s underneath the hood,” Chen said. “My hope is that through this content, we can bring more attention and awareness to the potential end users.”

The program is directed toward entry-level supply chain analysts and those in management roles who run backend operations.

With a finely-tuned curriculum that balances theoretical underpinnings with practical insights, the Supply Chain Analytics online certificate program prepares professionals for disruption and how the unpredictable can become the expected. Learn more and enroll today.

Cornell certificate equips leaders with natural language processing skills

In today’s digitized world, every action we perform generates data. A significant chunk of this information is in the form of text. Companies across industries grapple with colossal amounts of unstructured text data from diverse sources. Natural language processing (NLP) techniques make it possible to interpret, categorize and gain value from this otherwise overwhelming information, giving companies a competitive edge in an increasingly data-driven landscape.

Natural Language Processing with Python,” a new online certificate program from Cornell, was designed by Oleg Melnikov, visiting lecturer at the Cornell Bowers College of Computing and Information Science, to teach professionals the fundamentals needed to apply NLP in the workplace. Melnikov met with the eCornell team to discuss the importance of NLP knowledge and the ins and outs of the certificate program.

How does Natural Language Processing differ from machine learning?

“[NLP] is a topic that overlaps with machine learning. The difference is that machine learning doesn’t focus on text. It can have some examples related to text, but it’s primarily related to developing concepts of modeling, whereas in NLP, our domain is textual and we are focusing on solving language problems: text classification, translation, maybe building different representations of text in the mathematical domain. Machine learning steps in when we have converted text to numbers. Then we can apply machine learning algorithms.”

How are businesses currently leveraging NLP for their operations?

“This domain is expanding dramatically, and there are lots of projects in pretty much every domain. Different sectors, different companies, anything from McDonald’s to aviation, have some sort of textual interaction. All that requires some sort of summarization, some sort of categorization . . . where an individual doesn’t have to work with individual text but can step up at an aggregated level and process these massive text banks at scale.”

Who can gain the most value from your NLP program?

“NLP recently has been divided into two subdomains. One is what we’re introducing the students to: the classical techniques. Students who have not worked with NLP before would be good candidates for the certificate program. The courses are focused on preparing and developing students for the practical uses of natural language processing. There is another domain, which is a more modern, ChatGPT-like, neural-network-based NLP . . . that is for students who are more advanced with NLP skills.”

With textual analysis proving to be an integral tool across many industries, a working knowledge of NLP can help you and your workplace become more efficient. Expand your theoretical and technical expertise with NLP by enrolling in the Natural Language Processing with Python certificate program.

3 ways sustainable businesses can prepare for climate challenges

Wind turbines in a field against a background of a cloudy sky

From supply chain disruption to regulatory compliance pressure, companies experience bottom-line impacts of climate change every day. Accounting for environmental disruptions and transitions is essential to corporate risk management and resilience plans.

Sustainability and ecological transformation experts from Cornell University identified three strategies businesses can implement to thrive – and protect the planet – in a changing climate.

1. Limit the guesswork.

Forecasting climate change impacts on a company’s future requires a data-driven approach. Organizations can use current and projected temperature and weather trends to inform sustainability efforts. Leaders can also consult research and models from reputable sources such as the National Oceanographic and Atmospheric Agency and the Intergovernmental Panel on Climate Change to become better informed about the challenges – and opportunities – they may face. Research-based sustainable business practices enable companies to replace speculation with evidence-based predictions and solutions.

“Senior executives need to be fully aware of how climate change is shifting every assumption they may have about the future,” said Michael Hoffmann, former executive director of the Cornell Institute for Climate Change Solutions and professor emeritus in the College of Agriculture and Life Sciences. “Grasping how our world is fundamentally changing, and how to respond, is critical for their businesses as well as all of society.”

Corporations can expect more weather extremes that will cause delays, shortages and increased costs in the coming years. Hoffmann contends that it is critical to understand climate change’s bigger picture.

“Water scarcity, reduced crop yields, migration, heatwaves – we have witnessed the consequences of these issues on global business operations and consumers,” Hoffmann said. “Precedent should serve as a baseline for how businesses approach sustainability in the future.”

2. Avoid the copycat trap.

Given the uncertainty around best practices for a sustainable and regenerative future, corporate leaders might be tempted to duplicate the tactics of peers and competitors. Differences in operational size, industry, geography and customer base are important considerations in an organization’s efforts to reduce its effects on the climate and the climate’s effects on the organization.

According to Glen Dowell, the Henrietta Johnson Louis Professor of Management at the Johnson Graduate School of Management, there is no one-size-fits-all approach to climate change challenges for businesses.

“Fit your methods to at least two factors: what your company’s vulnerabilities and opportunities are, and the culture, structure and capabilities your company possesses,” Dowell said. “If your vulnerability stems largely from potential disruptions to a supply of a vital resource, you need to think both about how to secure a less vulnerable supply and possibly how to innovate to find a substitute.”

Dowell asserts that climate change reveals how interconnected our social and ecological systems are. The symbiosis is found in every company in every sector.

“For example, palm oil is sourced all too frequently by razing forests, leading to huge CO2 emissions and reducing the land’s ability to absorb CO2 in the future. If my company depended upon palm oil, I would be derelict in my duty to shareholders if I were not working tirelessly to secure a more sustainable source while simultaneously looking for a suitable replacement,” Dowell said. “For palm oil suppliers, developing a sustainable substitute would represent a significant business opportunity – a chance to gain massive sales to companies that need the product.”

3. Maintain a global and interconnected perspective.

Effective corporate sustainability initiatives involve employees from all business areas. Leaders can set policies and goals for emissions cuts, waste reduction and renewable energy investment, but success requires across-the-board adoption – especially in a time when consumers and investors increasingly expect companies to operate sustainably.

“The business case for sustainability is generally justified by increased profits, environmental benefits and a competitive advantage for early adopters,” said Danielle Eiseman, lecturer in the Brooks School of Public Policy. “However, as the effects of climate change become more widespread, the case for action becomes much more critical than what’s good for the bottom line.”

Eiseman encourages executives to assess the risks and consequences of climate challenges on their businesses through the lenses of individual and global impact.

“For informed decision-making, leaders need to comprehend the broader consequences like socio-economic implications and geopolitical shifts on a worldwide scale. Businesses operate within an ecosystem in which disruptions in one part of the world can have cascading effects throughout the supply chain and markets,” Eiseman said.

Learn how to seize the opportunities in sustainability.

Faculty from Cornell University have designed online certificate programs on a range of environmental, social and governance (ESG) topics, including sustainable business, corporate sustainability and equitable community change. A four-week Climate Change Leadership course from the Cornell College of Agriculture and Life Sciences is also available online through eCornell.

Cornell AI Strategy certificate prepares leaders to leverage new tech

In the era of artificial intelligence (AI), professionals across sectors are racing to strategize ethical and sustainable applications of the technology. Many organizations are actively pursuing AI knowledge not only to harness its potential but also to ensure responsible implementation.

Cornell’s new AI Strategy certificate program – authored by Soumitra Dutta, professor of operations, technology and information management in the Cornell SC Johnson College of Business – offers a nuanced curriculum for leaders who are ready to leverage the power of AI in various business contexts.

“Today virtually every single employee in an organization needs to understand something about AI. It doesn’t matter if it’s the senior executive in the boardroom, office worker or factory floor worker,” Dutta said.

The program, which is available through eCornell, includes six courses. Students begin with an introduction to AI then explore knowledge-based technologies, machine learning and data-based approaches to the technology. Later courses cover AI implementations across sectors, societal effects and the tech’s future prospects. Each module is designed to be applicable to the real-world concerns of any professional aiming to comprehend how AI integrates with business and society.

Upon completion of the program, students will understand how to:

  • Assess applications of AI in their organizations
  • Apply knowledge-based AI technologies to their organizations’ standard tasks
  • Address challenges by applying machine learning
  • Design strategies to implement AI systems across an organization
  • Examine the societal implications of AI in areas such as labor, privacy and ethics
  • Envision the development of strategies to preserve human dignity and agency while embracing the benefits of the technology

In light of the rapid evolution of AI, the program maintains a dynamic curriculum, emphasizing core principles and skills for comprehending the fast-changing discourse surrounding AI.

“It’s like an AI boot camp, ” said Dutta. “The program is sufficiently light on the technology side to give you enough background but sufficiently deep on the context and the strategy side. It gives you the technical background while hitting on all kinds of things happening in our world right now,” Dutta said.

AI is more than a tool; it’s a strategic necessity. Cornell’s AI Strategy certificate program prepares professionals to navigate the exciting yet complex future of the technology. Learn more and enroll today.

Crunching Numbers: Understanding the Power of Statistics

Hand holding pen pointing at graph

Imagine being able to transform raw data into actionable insights, shaping the direction of your business and your daily life. This power lies in understanding and applying statistics – the foundation of informed decision-making, the catalyst for impactful change and the key to unraveling the complexities of our world.

Cindy van Es, professor of practice at Cornell’s Dyson School of Applied Economics and Management and author of the Business Statistics certificate program, is expanding our comprehension of the study of statistics and its practical application in diverse fields. From agriculture to digital analytics, her work equips us with tools to navigate the complexity of both the corporate realm and our everyday lives, with statistics as our guide. Van Es shared her insights in the Keynote webcast “Statistics: What Everyone Should Know.”

How has statistics changed over the years?

“There are so many things after teaching it all these years, but . . . it’s present in every field these days. Even when I was going through education, it was very much the scientists, but it’s moved into so many fields now. The explosion I’ve seen over my career, from the very quantitative fields, to now: Every field has a metric. So it’s good to have a little idea of what goes behind some of these things.”

What are some surprising ways statistical information is used?

“When I think about the kinds of jobs my former students have now, they work for Airbnb, or Expedia, or Hilton or in finance. Even in marketing, now: A lot of stores will track your eyes . . . to see how long you look at a product, and they can correlate that data with the scanner data to see whether you bought it or not, and did the red label make you buy it more than the blue label . . . . There are experiments going on all around you, even when you’re not aware of it. Maybe you work in a nonprofit and you’re doing an amazing job, and it’s a very meaningful project, but in order to get funding, you may have to quantify why it’s amazing: What are the outcomes, and what are the metrics? There’s so much now: It’s kind of ubiquitous.” 

Which type of statistics is the most challenging to learn?

“Statistics has two branches: Descriptive and inferential. Descriptive is when you take a sample, you describe what you have and you ask the questions: Do I want to make a graph of this? Or do I want to make a table? Or calculate what we call ‘summary statistics?’ Most people are pretty good at that. Inferential is where you want to make an inference about a broader group, about a population. If you see a poll in the news, you’ll see a little plus-or-minus margin of error. That’s because they’re doing inferential statistics. When you see ‘this percent of people in the country think this,’ it’s based on a sample – so what you’re doing is making an inference. That part of statistics is a little harder for students and people in general, I think, because first of all, the language of inference is probability . . . understanding risk, understanding probabilities, the human mind really doesn’t think that way. So inferential is usually more challenging.”

Is artificial intelligence being used in statistical processes and interpretation of data?

“Each new technology – computers, and then supercomputers, and then desktops – influenced how people teach statistics and use techniques . . . . Now the merger is more with computer science and info science, as opposed to just being applied to agriculture, or medicine, or biology. Now the whole discipline is merging. Statistics hasn’t caught up with how to use [artificial intelligence] yet . . . statisticians are just starting to look at it.”

Harness the power of data interpretation in Cornell’s Business Statistics online certificate program. You’ll develop a dynamic set of skills that can heighten your confidence, fortify your decision-making, and catalyze meaningful change.

Drafted by eCornell writing intern Milan Lengyeltoti, with first round edits from marketing intern Justin Heitzman.

3 Ways to Sabotage Your Systems Architecture

Professor Oliver Gao studies air quality related to automobile emissions with researcher Shuai Pan.

As the adage goes, those who fail to plan, plan to fail. This is especially true in a rapidly evolving tech landscape. Systems architecture – the strategic art and science of designing complex foundations for software, hardware, networks, and even interactions between humans and machines – is a discipline that can help organizations plan ahead for growth, scale operations and reduce costs.

“We live in a time in which we will be confronted with complexities from various systems, ranging from healthcare to transportation. Our leaders and practitioners, executives and engineers, must be equipped with the right tools to address those complexities,” said Oliver Gao, director of systems engineering at Cornell, where he is also the Howard Simpson Professor in the School of Civil and Environmental Engineering.

Gao, faculty author of the Cornell Systems Architecture and Management program, identified three traps managers and developers should avoid to ensure their systems are successful.

1. Starting from scratch

“Systems architecture combines creativity and analytical rigor,” Gao said. “It is the most powerful way of thinking and making decisions to overcome challenges that are totally different from the challenges our ancestors faced.”

Yet, leaders do not have to reinvent the wheel. By leveraging current structures, organizations can extend the life of a system that has more function than flaws. This process can ensure that valuable data and performance is not degraded. While unproven methods for mapping form to function have higher risks for failure, building upon an established foundation can save time in development and deployment. Integrating with existing systems also preserves investments from the past.

According to Gao, a well-architected system makes an organization more agile and resilient against unknowns. To adapt and innovate faster, both engineers and team leaders should understand the frameworks already in place then make informed decisions on what can be enhanced or eliminated in response to business demands.

2. Disregarding data security

Information is the backbone of any system, but a single data breach can lead to demise: irrecoverable losses in finances, property and reputation. Interconnectivity in systems heightens the risk of leaving a door open to bad actors. Gao argues that security must be a core component of a systems architecture.

“This discipline is about thinking in systems rather than isolated components. A technical systems architecture must fit together strategically, just as every beam and wire must be positioned for stability and longevity in a structure such as a parking deck. Any vulnerability can result in significant harm to an organization, so systems need redundancies,” Gao said.

A secure system incorporates defenses against physical and digital threats, protections for proprietary data and recovery mechanisms. By taking a layered approach of encryption, auditing, training and more, Gao believes businesses can create sustainable systems.

3. Failing to future-proof

In an unpredictable digital ecosystem, solutions that work seamlessly today might not be equipped to handle tomorrow’s demands. An architecture that lacks scalability can cause costly disruptions as operational needs shift for a company. However, a well-planned architecture naturally evolves with an organization’s growth.

“It is important to listen to all stakeholders from the outset. It can’t be just the tech teams,” Gao said. “From the CEO to the finance team to the product managers to the front desk, everyone needs to be in the room to answer questions about their needs. Ignoring someone’s preferences can result in decreased productivity.”

Gao encourages systems architects to engage in a discovery process through interviews and research before starting a design to avoid wasteful allocation of budget, time and personnel resources on solutions that may not be effective or user friendly. Comprehensive understanding of organizational needs also ensures room for growth.

“Your company’s latest product offering could be quite different from earlier offerings. You might have to hire more staff. A system might not adjust to these changes immediately. If you’ve brainstormed how the future could look and tested for flexibility in the systems architecture, your solutions will be prepared to bend but not break,” Gao said.

Planning your systems architecture

As a leading expert in urban infrastructure, transportation, and environment systems analytics for smart communities, Gao has developed a Systems Architecture and Management program to help organizations understand the value of systems architecture related to performance, lifecycle cost, schedule and risk. He works directly with organizations to help their leaders examine their systems, characterize and prioritize stakeholders using network theory and more.

“Investing in systems architecture is investing in the foundation of an organization, enabling it to grow efficiently and successfully,” said Gao. “Systems architecture ensures that technology aligns with business objectives and paves the way for the future.”

The Systems Architecture and Management program is one of Cornell’s several custom live educational opportunities for corporations, nonprofits and other organizations. Learn more about the university’s enterprise programs online.

Cornell introduces new AI-focused Board Governance program

Cornell live immersion program participants engage in discussion

Blending resilience and risk is essential for companies that intend to survive today’s tech innovations, economic uncertainty and political pendulum swings. The greater the challenges, the greater the demand for leaders who can deliver an effective mix of foresight and strategic oversight.

Board Governance: Navigating Emerging Technologies and More in a Complex World, a new Cornell Tech immersion program slated for this fall, is set to prepare corporate board members for fast-paced evolutions in artificial intelligence (AI), geopolitics, cybersecurity, supply chains, sustainability and other areas driving the future of commerce.

Read the full story on the Cornell Chronicle.

Bringing New Science to Market

Medical supplies and drugs, including a syringe, surgical mask, and pills

Medical innovation is reaching new heights every year. What scientific breakthroughs can we expect on the market in the coming decade? What challenges will we face in adopting them?

Professor Sean Nicholson, director of the Cornell Sloan Program in Health Administration, welcomed Wyatt Gotbetter, SVP and worldwide head of Parexel Access Consulting, and Dr. Gregory B. Franz, MD, MPH, MHA, hematologist and medical oncologist at the Kirkland Cancer Center, to explore answers to these questions in the recent Keynote webcast “Bringing New Science to Market: Innovation, Adoption, and Health Policy Challenges.”

Biotech and pharmaceutical firms spend about $80 billion each year on research and development in order to try to bring new therapies to the market. What is in the pipeline that might have a big positive effect on the health of the population in the future?

Gotbetter: “If we think just about the past five years, and of course that includes the pandemic, I think the rate of innovation and the number of launches has been remarkable. We can’t have this discussion without acknowledging the validation and the importance to all of us of the RNAi vaccines from BioNTech and Moderna. Moderna, on the heels of that success and being flush with sales of their COVID vaccine, is really advancing a number of therapeutic products as well as vaccines – really advancing their RNAi technology into the therapeutic space and oncology specifically.

In the same time, we’ve seen the approval of a couple of CAR-Ts truly advancing life-saving therapy in hematology and oncology. I think we’ll see gene therapies becoming safer and easier to manufacture, hopefully at lower costs. There’s just a pipeline of literally hundreds of programs where we’ll see gene therapy go from rare disease and disease that has very, very high morbidity perhaps into things managed more chronically with small molecule drugs – like heart failure.”

We have a couple of CAR-T therapies on the market that are Food and Drug Administration (FDA) approved. Are there similar kinds of classes of compounds that have yet to be approved that you think might potentially have a similar health impact?

Franz: “Leveraging the immune system to identify and kill cancer cells – that’s really what’s going on here. This is T cells doing what T cells do against cancer cells. I know that’s a very simple explanation. It’s very difficult to develop these compounds and to do this safely, but I think that’s where the money and the future is.”

It takes a long time, and it’s very expensive for biotech and pharmaceutical firms to run clinical trials and, even preceding that, to identify compounds that are promising enough to start a clinical trial. The current estimate is about $2.6 billion in investment across a portfolio of compounds in order to statistically assure a company that they’re going to have one approved compound. Where do companies come up with that money, and in the current climate, is it difficult for companies to raise the funds they need in order to invest in those drugs?

Gotbetter: “That $2.6 billion figure also includes the cost of failure. Even if we think about a successful drug compound, if you boil down the numbers, hundreds and hundreds of drug candidates will be considered before you start your phase one and then roughly one in ten of those will make it through to approval. It’s fraught with risk. But even if you could streamline that process, you’re probably looking at hundreds of millions to a billion dollars.

The amount of money that’s poured into the biotech sector over the past few years has been remarkable. We’ve seen, though, a massive sea change in the past year. Biotech has been the engine of discovery and innovation for large pharmaceutical companies. The largest companies in the world that certainly have formidable R&D engines employing thousands of people still turn to biotech to find innovation, to find a compound that has been tested, that shows a proof of concept, and can move forward.

The headwinds of the past year or two – interest rates and some of the perceived threats of the Inflation Reduction Act, which could reduce pricing power of the industry – has really slowed down [venture capital] funding.

I think what that means is that probably the rate of innovation will slow down a little bit in the sense that there may be fewer programs being pursued simultaneously, so a company may really focus on the crown jewels instead of many at once. Then biotech may again have to be more reliant on Big Pharma once they’re in the middle of their development versus a period where they probably could see funding to go all the way through.”

What are the factors that make a drug widely adopted?

Franz: “In the medical oncology world, it’s really all about safety and efficacy. Is the drug difficult to give? Does the patient have a lot of adverse side effects? How do you manage those side effects? But most importantly, you’re looking at endpoints: PFS, or progression-free survival, and OS, or overall survival. Duration of response and response rate are biggies and, of course, the toxicity profile. All those together are important. The better the PFS and OS, the more successful the drug is going to be.”

Are biotech and pharmaceutical firms doing anything to try to run their trials differently – to be less expensive, to be shorter, to have higher probability of approval?

Gotbetter: “The FDA provides a rubric that says for very life-threatening diseases, it will work with the industry sponsor to find a way to streamline the therapy. We have names for that in the U.S like breakthrough therapies and accelerated pathways, where you get more support and guidance from the regulatory agency, but you’re also partnering with them along the way to find a way to expedite the study.

There’s a lot of companies that are using all sorts of AI, computational methods and synthetic biology to [speed up the trial process].”

Historically, clinical trials have been dominated by white men. Are biotech and pharmaceutical firms trying to diversify those trials? What are the implications potentially of a more representative group of patients in the testing phase?

Gotbetter: “There are mandates coming from the FDA and other governments, and I think very sincere efforts from the pharma industry and from clinical research organizations who enroll and operationalize the studies to really bring diversity into studies. There’s an awareness in society for many reasons, for many historical wrongs, we need to bring more diversity into everything we do. It’s to really ensure that when we study a drug, we’ll be able to show efficacy in different populations because we’re not all the same. Historically, if you were to develop a drug for people of European descent, across the globe in Asian markets, they would want to know that there was a study being done in populations for which the results were meaningful for them. As we take that to other populations, to different age groups, different genders, it’s the right thing to do.”

 

This post has been edited for length and clarity.

Want to learn more about the future of biopharma? Register for Cornell’s Biotech and Pharmaceutical Management Immersion Program and watch the full Keynote “Bringing New Science to Market” webcast online.