How pharma leaders talk about ethics in a highly criticized industry

Earlier this week, NYU bioethics professor Arthur Caplan gave PharmaVoice a rundown of what he felt were the most important ethical quandaries in the biopharma realm. From pricing and patient groups to diversity and drug development, the considerations for pharma companies might appear like criticism. In fact, they are just better ways of doing business, according to Caplan.

But talking about ethics from an academic perspective and employing them in the real world are two different endeavors, unless they can be brought together.

Today we’re exploring the other side — how pharma leaders take ethics into account on a daily basis, and what that means for patients. While the industry’s reputation waxes and wanes, medical need continues to grow, and these leaders are charged with not only assuring the company’s bottom line is met, but that it’s met with integrity and patients’ needs in sight.

Here are some of the concepts these leaders evoked when it comes to ethics.

The credo

Companies as large as J&J need a guiding light to form an ethical direction — especially when faced with major allegations such as the concerns over its use of talc in baby powder. But the company maintains that patient safety is always a core consideration. 

“It’s an integral part of our decision making,” said Dr. Craig Tendler, vice president of oncology clinical development and global medical affairs at Johnson & Johnson Innovative Medicine (formerly Janssen). “Johnson & Johnson has a credo … that everything we do has to be for the benefit of patients. It is a core element of our plans, our decision making and everything we do.”

And for big companies with profits and shareholders to manage, it’s especially important to ensure that the patient is the one who benefits, said Dr. Daejin Abidoye, head of solid tumors, oncology development at AbbVie.

“Understanding from a patient perspective what’s important … and the overall experience for the patient, whether it’s in the area of hair loss, dermatitis, weakness, fatigue — this is their experience, right?,” Abidoye said. “And it’s important as we develop these medicines, we think not only about what effect our medicines are going to have on the cancer, but what effect it’s going to have on the patient.”

‘Bad actors everywhere’

For consultants working with the industry, the calculation for which companies could be problematic is simple.

“There are bad actors everywhere, and we’re not going to work for them,” said Leslie Orne, CEO and president of Trinity Life Sciences, which is focused on launch strategies for the industry. 

Orne spoke about opioids and drug pricing as deal breakers for the company’s consulting business.

“We have a core set of values … and we have to stay on our toes about that,” Orne said. “I look at other companies engaging with some of those bad actors, and I won’t name names, but you know who they are, and they’re working on two sides of very delicate issues.”

The AI revolution

Artificial intelligence poses new ethical challenges around safe guarding data and privacy. The Biden administration has developed standards to ensure that federal funding goes to protecting private citizens, but with biopharma companies in control of their own budgets, it can’t be confirmed the industry will stay in line.

For Terri Shieh-Newton, partner and member at the law firm Mintz, there are many issues to consider when it comes to the ethics of AI. Who is setting the standards? Are there ethicists on board? What biological lines can even be drawn? Where will those lines be? How does funding work?

And ultimately, how much weight do ethics get against other biological or financial considerations?

“Some AI developers try to balance the attention to ethics with efficiency by incorporating a rules-based approach for what is ethical and what is not as part of their algorithm,” Shieh-Newton said in an email. “These rules are combined … with the algorithms that provide greater accuracy. One challenge is to define the rules of ethics for the program and then make the determination of how much weight should be given to the ethical rules as part of the machine learning model that also focuses on technical accuracy.”