In less than a year, Jim Cafone and his team at Pfizer were able to create a whole new supply chain for the COVID vaccine. Now, with the new anti-viral pill, they look to do it all over again.
Photo caption: To produce the COVID-19 vaccine, Pfizer miniaturized the manufacturing process, creating what are essentially “factories in a box."
Imagine that your company is gearing up to launch a new product. Take a minute to consider all the complexities and hurdles that a new product introduction generally involves from a supply chain perspective. Now imagine that this product is based on brand new technology that would require manufacturing processes unlike the ones that your company currently uses. And that this product is extremely delicate and would require a specialized temperature-controlled transportation and distribution network.
Now imagine that the customer base for this product numbers is in the billions—spread all over the world. And that these billions of customers are eagerly awaiting (and closely scrutinizing) your new product—the eyes of the world are fixed upon you. Now imagine that you had to design that supply chain in less than a year.
That was the daunting and pressure-filled challenge Jim Cafone and his team at the pharmaceutical giant Pfizer faced when they were working to create the supply chain for the COVID-19 vaccine in conjunction with their partner BioNTech.
According to Cafone, vice president of network design and performance for Pfizer Global Supply, there was never any doubt that the company would accept this challenge. As one of the world’s largest vaccine manufacturers, unlocking a vaccine for COVID-19 and getting it to as many people as possible, as fast as possible, felt like a moral obligation. To meet this challenge, Pfizer was open to collaborating with any and all outside partners. It quickly became apparent that one of the most promising ways to defeat the virus lay with the new messenger RNA (mRNA) technology that was being developed by the biotechnology company BioNTech. At that time, Pfizer had an extensive manufacturing and distribution network for vaccines and pharmaceuticals, but not one piece of it was based on mRNA. The whole process and network would have to be created essentially from scratch.
In this interview with CSCMP’s Supply Chain Quarterly Executive Editor Susan Lacefield, Cafone talks about how his team rose to meet that challenge, which included changing the very way that they worked.
NAME: Jim Cafone
TITLE: Vice president, network design & performance, Pfizer Global Supply
RESPONSIBILITIES: Business development, supply network design, production system, performance reporting, analytics, decision science for worldwide supply, global manufacturing network design for BioNTech/Pfizer COVID-19 vaccine
PREVIOUS EXPERIENCE: Ford Motor Company, PricewaterhouseCoopers, Wyeth Pharmaceuticals, and Pfizer
EDUCATION: Bachelor’s degree in industrial engineering and master’s in mechanical engineering from University of Rhode Island; master’s in technology management from University of Pennsylvania
When you were developing the supply chain for the COVID-19 vaccine, did Pfizer have any previous experiences that you could draw upon?
As one of the largest vaccine manufacturers, we of course had experience with building out supply chains but not at the same scale. Nobody builds a manufacturing network for a pandemic. In a world with a population of 7.6 to 7.8 billion people, you are talking about a need that obviously has never been seen before. Up until COVID, the No. 1 vaccine in the world was a product by the name of Prevnar [used to prevent diseases caused by the pneumococcal bacteria], and in 2019, we manufactured roughly 200 million doses of that.
But, you know, Prevnar uses a different sort of technology than the COVID vaccine. We were discussing whether to use what I would classify as “tried and true” traditional vaccine technology or move to the mRNA platform. We chose the mRNA platform due to the confidence we had with our partner.
Making that move to the mRNA technology required a lot of innovations and new developments. Were there two or three challenges that were particularly difficult to solve, or that really stood out for you?
In my view, there were three major challenges. One was building out an mRNA manufacturing supply chain that had not existed anywhere in the world. There just wasn’t enough equipment in the world if we used standard approaches. The type of scale that we needed just didn’t exist. So, we had to fundamentally reinvent the manufacturing process, which included not only making the mRNA but also filling and finishing vials.
Challenge number two was building out a network of innovative collaborators. We have roughly 280 components coming in from 85 suppliers from 19 different countries, and we had to build a network out using these collaborators.
Then the third thing was the whole logistics side, which was building a shipment device that could handle deep frozen vaccines. mRNA doesn’t like heat at all. So, we optimized [our supply chain] on speed, we optimized on deep frozen.
So those were the three: reinventing the manufacturing process, developing a brand new manufacturing network with a lot of innovative players, and reinventing deep-frozen distribution on a global scale.
Right, and that global piece has got to be really difficult because it is one thing to keep things frozen in, say, the United States or Europe. It is another thing when you are distributing in remote parts of Africa or Asia, I imagine.
Exactly. The shipping container that we designed was meant also to be a portable storage device. It wasn’t a situation where upon receipt you had to immediately open it up. We designed it so that it kept temperatures consistent up to, I want to say, about ten days.
We wanted it to be easy and efficient to pack. We needed a product stable for up to ten days in remote locations, and we wanted it to be returned or reused. So that was like another medical innovation.
All during that time too, we took 50% of our cycle time for manufacture out. We expanded wherever we could in our network to get more volume. We put $2 billion dollars’ worth of capital at risk in order to optimize its speed. In 2021, we manufactured 3 billion doses, and 1 billion of those went to low- and middle-income countries. Our focus was on health care equity regardless of where you were in the world.
Another thing that Pfizer accomplished was redesigning the whole manufacturing process to be very micro. How were you able to accomplish that?
[Even before COVID,] the entire manufacturing process had been getting what I would call miniaturized. That miniaturization is based on the fact that as the industry starts to attack more rare diseases, you don’t need big manufacturing infrastructures anymore. You need small, nimble manufacturing infrastructures.
What was interesting with the COVID vaccine is we needed massive scale, but we couldn’t find 6-, 12-, or 20-thousand-liter vessels at that time to produce this mass volume. They just didn’t exist in the world. Again, you are talking about a patient population of potentially 8 billion people. So what we decided to do was take a page out of both books and look at how do we miniaturize and instead of scaling up, how do we scale out.
The answer is basically a miniaturized manufacturing plant. What we did is we designed those [miniaturized plants] so that you could start to create racks of them. Almost like you see in a data center. If you go into a data center, you may see a rack of ten servers, but if you go into an Amazon data center you may see thousands of feet of servers, right? As you add [servers], you are adding computer power. As we were scaling out [our miniaturized plants], we were adding in volume. We redesigned the entire process to be like a factory in a box, and then you could start to replicate those [factories] in a way that is fundamentally equivalent to server arrays in a data center. That is how we largely did it.
In the midst of all that, how did you solve the challenge of building a network of suppliers to collaborate with you on a very new technology?
The genetic sequence for the SARS virus was updated on January 12, 2020. This was when we were approached by BioNTech with their mRNA COVID technology. The way that I describe it is, it was a great marriage. One and one together can accomplish more. They had great science. We had the best development organization, and I would argue the best supply chain organization. (Now, I’m biased, of course.)
Once we went with mRNA technology, then we approached our suppliers that were in the mRNA space as rapidly as possible. The challenge we had was that mRNA was largely an academic exercise, a medical school exercise at that time. Suppliers were really great at supplying those industries, but they were supplying relatively small amounts. Then we were calling up and saying, “Hey we need plasmids, or capping agents, or some of the other materials. Can you send us some of this material?” They would then ask us how many liters we would need, and we were saying, “No. No. No. We need tens of thousands of liters.”
We worked exceptionally closely with all of our suppliers in an open, innovative fashion in order to get the volume. When we couldn’t get the volume by helping them troubleshoot, in some cases, we brought the volume into our network.
Do you feel like the crisis of the pandemic really made that collaboration with external partners a little easier?
I definitely think there was a different sense of purpose. Now, of course every pharmaceutical is important to some patient out there, but this one had an even larger sense of purpose. I also think our suppliers saw that sense of purpose in our light-speed culture, which grew pretty rapidly. It was all about speed. It was all about innovation. It was all about breaking down bureaucracies. It wasn’t about governance and meetings and Power Points anymore. It was all about the breakthrough mindset.
It was an interesting cultural element because my team designed the network during meetings that I wasn’t in. I was perfectly happy not being in them because people were accountable for getting the work done. I never was on a call where there were more than maybe a dozen people at the meeting. If you were at the session, you were there for a purpose. You weren’t there just to listen or to hang on. You know, we have all been on conference calls unfortunately in our careers where you jump on and there are 50 people on there and 30 are trying to get a word in. Again, it was all about speed, agility, innovation, breakthrough mindset, which means by default, you have to feel comfortable not being a part of everything. Let the organization as a whole do its work.
And now Pfizer is beginning to ramp up distribution for the Paxlovid antiviral pill. How is that different from what your efforts have been for the vaccine?
First of all, we have been fortunate to get hit by a bolt of lightning twice now in the last year. The first one was the corona vaccine, and the second one now is Paxlovid.
Fundamentally, we are doing it all over again. The challenge you have is the volume because now you are not dealing in biological processes; you are dealing in physical chemistry processes. What we are working through now basically is how quickly can we ramp up once again. To put it in perspective, the highest volume of pharmaceuticals we ever produced was for Lipitor, the cholesterol-lowering agent, in 2010. It was one of its final years of patent protection, and we manufactured 250 metric tons of active pharmaceutical agents. That is the largest drug we have ever produced by volume. For Paxlovid, this year we need to produce 500 metric tons, so two Lipitors. By the way, that Lipitor [production volume] that I talked about was during year eight or nine of its life cycle.
Right, so you had already figured it all out.
We’d figured it all out, and we had seven generations of process improvement. With [Paxlovid], we’ve got to produce 500 metric tons, and we need to do that within the first year of launch. We are assembling a network of active pharmaceutical ingredient suppliers from all over the globe, including our own assets from product tableting operations and packaging operations. Again, everything we can do for speed and agility.
One last question: How do you keep your team from not burning out?
We are fortunate. Pfizer has helped everyone with all sorts of tools to take a break. We have been focusing on doing everything we can to get people to have a proper work/life balance in this difficult time. We have been focusing on mindfulness. We have been focusing on taking the right breaks at the right time.
The problem we have fundamentally is people want to solve these problems. We didn’t have the issue of getting people into our manufacturing plants. We have people that wanted to come in because, even if they aren’t making the vaccine or Paxlovid, they are still making a lot of medicines that people need. We actually have trouble getting people to stop working and to feel okay with taking a break. It’s clear that our people have a commitment to Pfizer’s Purpose: “Breakthroughs that change patients’ lives.”
The launch is based on “Amazon Nova,” the company’s new generation of foundation models, the company said in a blog post. Data scientists use foundation models (FMs) to develop machine learning (ML) platforms more quickly than starting from scratch, allowing them to create artificial intelligence applications capable of performing a wide variety of general tasks, since they were trained on a broad spectrum of generalized data, Amazon says.
The new models are integrated with Amazon Bedrock, a managed service that makes FMs from AI companies and Amazon available for use through a single API. Using Amazon Bedrock, customers can experiment with and evaluate Amazon Nova models, as well as other FMs, to determine the best model for an application.
Calling the launch “the next step in our AI journey,” the company says Amazon Nova has the ability to process text, image, and video as prompts, so customers can use Amazon Nova-powered generative AI applications to understand videos, charts, and documents, or to generate videos and other multimedia content.
“Inside Amazon, we have about 1,000 Gen AI applications in motion, and we’ve had a bird’s-eye view of what application builders are still grappling with,” Rohit Prasad, SVP of Amazon Artificial General Intelligence, said in a release. “Our new Amazon Nova models are intended to help with these challenges for internal and external builders, and provide compelling intelligence and content generation while also delivering meaningful progress on latency, cost-effectiveness, customization, information grounding, and agentic capabilities.”
The new Amazon Nova models available in Amazon Bedrock include:
Amazon Nova Micro, a text-only model that delivers the lowest latency responses at very low cost.
Amazon Nova Lite, a very low-cost multimodal model that is lightning fast for processing image, video, and text inputs.
Amazon Nova Pro, a highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks.
Amazon Nova Premier, the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models
Amazon Nova Canvas, a state-of-the-art image generation model.
Amazon Nova Reel, a state-of-the-art video generation model that can transform a single image input into a brief video with the prompt: dolly forward.
Economic activity in the logistics industry expanded in November, continuing a steady growth pattern that began earlier this year and signaling a return to seasonality after several years of fluctuating conditions, according to the latest Logistics Managers’ Index report (LMI), released today.
The November LMI registered 58.4, down slightly from October’s reading of 58.9, which was the highest level in two years. The LMI is a monthly gauge of business conditions across warehousing and logistics markets; a reading above 50 indicates growth and a reading below 50 indicates contraction.
“The overall index has been very consistent in the past three months, with readings of 58.6, 58.9, and 58.4,” LMI analyst Zac Rogers, associate professor of supply chain management at Colorado State University, wrote in the November LMI report. “This plateau is slightly higher than a similar plateau of consistency earlier in the year when May to August saw four readings between 55.3 and 56.4. Seasonally speaking, it is consistent that this later year run of readings would be the highest all year.”
Separately, Rogers said the end-of-year growth reflects the return to a healthy holiday peak, which started when inventory levels expanded in late summer and early fall as retailers began stocking up to meet consumer demand. Pandemic-driven shifts in consumer buying behavior, inflation, and economic uncertainty contributed to volatile peak season conditions over the past four years, with the LMI swinging from record-high growth in late 2020 and 2021 to slower growth in 2022 and contraction in 2023.
“The LMI contracted at this time a year ago, so basically [there was] no peak season,” Rogers said, citing inflation as a drag on demand. “To have a normal November … [really] for the first time in five years, justifies what we’ve seen all these companies doing—building up inventory in a sustainable, seasonal way.
“Based on what we’re seeing, a lot of supply chains called it right and were ready for healthy holiday season, so far.”
The LMI has remained in the mid to high 50s range since January—with the exception of April, when the index dipped to 52.9—signaling strong and consistent demand for warehousing and transportation services.
The LMI is a monthly survey of logistics managers from across the country. It tracks industry growth overall and across eight areas: inventory levels and costs; warehousing capacity, utilization, and prices; and transportation capacity, utilization, and prices. The report is released monthly by researchers from Arizona State University, Colorado State University, Rochester Institute of Technology, Rutgers University, and the University of Nevada, Reno, in conjunction with the Council of Supply Chain Management Professionals (CSCMP).
Specifically, 48% of respondents identified rising tariffs and trade barriers as their top concern, followed by supply chain disruptions at 45% and geopolitical instability at 41%. Moreover, tariffs and trade barriers ranked as the priority issue regardless of company size, as respondents at companies with less than 250 employees, 251-500, 501-1,000, 1,001-50,000 and 50,000+ employees all cited it as the most significant issue they are currently facing.
“Evolving tariffs and trade policies are one of a number of complex issues requiring organizations to build more resilience into their supply chains through compliance, technology and strategic planning,” Jackson Wood, Director, Industry Strategy at Descartes, said in a release. “With the potential for the incoming U.S. administration to impose new and additional tariffs on a wide variety of goods and countries of origin, U.S. importers may need to significantly re-engineer their sourcing strategies to mitigate potentially higher costs.”
Grocers and retailers are struggling to get their systems back online just before the winter holiday peak, following a software hack that hit the supply chain software provider Blue Yonder this week.
The ransomware attack is snarling inventory distribution patterns because of its impact on systems such as the employee scheduling system for coffee stalwart Starbucks, according to a published report. Scottsdale, Arizona-based Blue Yonder provides a wide range of supply chain software, including warehouse management system (WMS), transportation management system (TMS), order management and commerce, network and control tower, returns management, and others.
Blue Yonder today acknowledged the disruptions, saying they were the result of a ransomware incident affecting its managed services hosted environment. The company has established a dedicated cybersecurity incident update webpage to communicate its recovery progress, but it had not been updated for nearly two days as of Tuesday afternoon. “Since learning of the incident, the Blue Yonder team has been working diligently together with external cybersecurity firms to make progress in their recovery process. We have implemented several defensive and forensic protocols,” a Blue Yonder spokesperson said in an email.
The timing of the attack suggests that hackers may have targeted Blue Yonder in a calculated attack based on the upcoming Thanksgiving break, since many U.S. organizations downsize their security staffing on holidays and weekends, according to a statement from Dan Lattimer, VP of Semperis, a New Jersey-based computer and network security firm.
“While details on the specifics of the Blue Yonder attack are scant, it is yet another reminder how damaging supply chain disruptions become when suppliers are taken offline. Kudos to Blue Yonder for dealing with this cyberattack head on but we still don’t know how far reaching the business disruptions will be in the UK, U.S. and other countries,” Lattimer said. “Now is time for organizations to fight back against threat actors. Deciding whether or not to pay a ransom is a personal decision that each company has to make, but paying emboldens threat actors and throws more fuel onto an already burning inferno. Simply, it doesn’t pay-to-pay,” he said.
The incident closely followed an unrelated cybersecurity issue at the grocery giant Ahold Delhaize, which has been recovering from impacts to the Stop & Shop chain that it across the U.S. Northeast region. In a statement apologizing to customers for the inconvenience of the cybersecurity issue, Netherlands-based Ahold Delhaize said its top priority is the security of its customers, associates and partners, and that the company’s internal IT security staff was working with external cybersecurity experts and law enforcement to speed recovery. “Our teams are taking steps to assess and mitigate the issue. This includes taking some systems offline to help protect them. This issue and subsequent mitigating actions have affected certain Ahold Delhaize USA brands and services including a number of pharmacies and certain e-commerce operations,” the company said.
Editor's note:This article was revised on November 27 to indicate that the cybersecurity issue at Ahold Delhaize was unrelated to the Blue Yonder hack.
The new funding brings Amazon's total investment in Anthropic to $8 billion, while maintaining the e-commerce giant’s position as a minority investor, according to Anthropic. The partnership was launched in 2023, when Amazon invested its first $4 billion round in the firm.
Anthropic’s “Claude” family of AI assistant models is available on AWS’s Amazon Bedrock, which is a cloud-based managed service that lets companies build specialized generative AI applications by choosing from an array of foundation models (FMs) developed by AI providers like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself.
According to Amazon, tens of thousands of customers, from startups to enterprises and government institutions, are currently running their generative AI workloads using Anthropic’s models in the AWS cloud. Those GenAI tools are powering tasks such as customer service chatbots, coding assistants, translation applications, drug discovery, engineering design, and complex business processes.
"The response from AWS customers who are developing generative AI applications powered by Anthropic in Amazon Bedrock has been remarkable," Matt Garman, AWS CEO, said in a release. "By continuing to deploy Anthropic models in Amazon Bedrock and collaborating with Anthropic on the development of our custom Trainium chips, we’ll keep pushing the boundaries of what customers can achieve with generative AI technologies. We’ve been impressed by Anthropic’s pace of innovation and commitment to responsible development of generative AI, and look forward to deepening our collaboration."