Translating Knowledge Management Into Operational Excellence

Driving Operational Excellence

In this installment of QbDVision’s Knowledge Management Lab, we discuss how developing an internal digital knowledge management capability for your organization can translate into operational excellence based on agile management principles.

We see the objective of achieving organizational agility for CMC, MSAT, and Process Development teams as a critical factor in the future success of the pharma/biotech industry. The path to organizational agility and overall operational excellence starts with knowledge management as part of a broader digitization effort. Empowered teams that are moving quickly and focused on outcomes must share a collective intelligence. Traditional hierarchical approaches to organizational management and information sharing can kill an agile culture. To move fast, teams need a way to collect, enrich, and share information broadly and without delay.

Did you know that pharma/biotech companies use less than 4% of their data? This statistic demonstrates that we have plenty of opportunities for improvement. While knowledge management initiatives can improve data utilization, they have to go beyond simple aggregation of content (“the SharePoint approach”). In this whitepaper, we offer some practical suggestions on how to get started with knowledge management and explain why this approach ultimately improves your process understanding and overall process intelligence.

While there isn’t a one-size-fits-all approach to achieving operational excellence, starting here will provide an actionable path to building organizational excellence and getting higher quality products to patients faster. Something we’re all after.

Start With Knowledge Management

A primary objective of the product development lifecycle is to develop a scalable manufacturing process that is well-controlled and consistent in the level of product quality to ensure patient safety and efficacy. Traditionally, this process has been linear and reactive with a focus primarily on quality compliance. Recent initiatives, such as Right First Time and Pharma 4.0, have focused on re-thinking this development process so that it is proactive, holistic, driven science and data, and defined by digitally-enabled best practices such as Quality-by-Design (QbD). To this end, knowledge management (KM) and its close counterpart, quality risk management (QRM), are seen as key elements of these new initiatives.

This need for systematic knowledge management has gained further traction with the creation of the BioPhorum Knowledge Management initiative, which seeks to provide a starting point for building true knowledge management (KM) capability in the pharma/biotech industry. This initiative, led by experts from across the industry, seeks to make the drug development journey better, cheaper and faster through improved quality, cost, speed, and agility.

A suggested hierarchy of knowledge management presents a familiar theme focusing on technology, process, and people. This hierarchy has, as its foundation, the proper IT infrastructure to adequately capture the information (content) generated by an organization during its development activities throughout the product life cycle. Ideally, the combination of IT infrastructure with centralized information will enable business processes based on best practices. These layers then come together to enable people to work smarter and faster, fostering agility, creativity, and leadership. Of course, this is easier said than done because just building databases on top of servers to aggregate information is not enough. The solutions that capture the information need to organize and contextualize the information to support key business processes and enable best practices. The fulfillment of these additional requirements is key to the conversion of information into institutional, actionable knowledge. This construct is a bit general, but it can be further specified starting with the deployment of novel SaaS applications to capture structured content enabling QbD/ICH workflows that drive shared process understanding.

It could be further argued that the establishment of a knowledge-based culture is not a linear hierarchy or a sequential set of activities (i.e. IT → Information → Process → People). Instead, each layer is cultivated in parallel with the others, starting with a small core of people (Agile teams) utilizing technology to enable more efficient processes, and then growing as Agile principles and more teams proliferate within the organization.

Is it Data, Information, or Knowledge?

The process development, manufacturing, and validation stream of activities for a new drug product average about 7-8 years in total cycle time. The total product life cycle can last over 20 years. Over that time, vast amounts of data are generated about the formulation, manufacturing process, recipes, materials, equipment, and more. Where does all this data end up?

For pre-commercial activities (PD/PV), it gets dispersed primarily in spreadsheets, reports, emails, and batch records which are converted into controlled documents and then stored in electronic quality management systems (eQMS). The process of aggregating the data into descriptive reports provides much-needed context transforming the content into more insightful information.

However, a fundamental problem still remains. At the end of a development cycle, an organization will have thousands of pages of information and data stored as unstructured narratives in various locations. When it is time to draft regulatory submissions or work with auditors and inspectors, a significant amount of personnel time is required to manually extract the information needed (if it can even be found) and provide context around it. The challenge becomes even more acute when it is time to complete the highly complicated process of technology transfer.

Aggregating unstructured data begins the process of converting data into information. But, often, the sheer volume of this information blocks the transition from information to knowledge.

This is a ubiquitous problem that is not specific to the pharma/biotech industry. An entire industry has been created to help companies mine and aggregate their vast amounts of data. However, we see this as complexity layered on top of complexity, and it keeps this tradition of dispersed technology solutions in place. What if we go the other way and create a structured environment where information can be put where it belongs, with the appropriate context as it is generated? Are there specific advantages conferred by this approach? Indeed there are the following with structured data approaches:

  • provides context to content, turning data into information
  • increase visibility and transparency by improving accessibility
  • create reusable artifacts making knowledge institutional.

Does the specific structure of information matter?

Throughout the pharma/biotech industry today, the fundamental unit of information is “the document.” This is akin to saying that a sand grain is the fundamental unit of matter. We all know that documents have a lot of smaller increments of information, much like the sand grain is composed of many atoms and other subatomic particles.

Continuing with this analogy, what if we define the requirement as the atomic unit of information. Requirements are then defined, assembled, and linked to form a web of information. These can be patient requirements, product requirements, and process requirements with related information such as risk, acceptance criteria, manufacturing data, and so on, all linked together. This approach creates a multi-dimensional data set where each element represents a node that can be linked to other nodes.

This multi-dimensional data set can be probed in any subset of dimensions to understand the critical relationships within the subset of interest. Now we can begin converting information into knowledge.

Driving Best Practices

The structured, requirements-based approach to knowledge management presents significant opportunities to vertically integrate information in ways not previously possible with a document-based system.

Stage 1 of this framework starts with the requirements-based structure where patient, product, and process requirements can all be defined and tracked individually.

Stage 2 of vertical integration brings the tools of quality risk management (QRM) as described in ICH Q9 and Q10, into the framework. With QRM integration, each requirement can be separately assessed for risk. Furthermore, process requirements can be digitally linked to product requirements, and product requirements can be linked back to patient safety/efficacy attributes, creating risk-based traceability as recommended throughout ICH Q8 – Q10.

Stage 3 integrates raw material and manufacturing data into the multidimensional data set. This data can be analyzed to identify trends and assess process capabilities. The integration of process data drives a key feedback loop enabling a consistent focus on those areas which need the greatest attention.

Stage 4 folds in the tangible assets of production, specifically raw materials, components, and equipment. Visibility into these dimensions is often limited and not easily accessible. By tracking these assets with respect to qualification and performance and how they link to suppliers and supplier risk, a comprehensive view of the entire production process comes into focus (ICH Q10).

Stage 5 uses all of the other stages to justify the control strategies identified for the validated process. With the strong, foundational knowledge base represented by Stages 1-4, it becomes easier to define a robust control strategy and defend that strategy going forward. This knowledge base also simplifies the impact assessment of changes to the process post-approval.

“To QbD or Not to QbD?”

It is a central question always considered during process development in pharma and biotech. Quality-by-Design (QbD) is a philosophy of product development that seeks to design quality into a product (as opposed to testing quality into a product) and is relevant when the product is being designed and the process to manufacture it is being developed. This approach moves to the Lean Manufacturing and Six Sigma methodologies for continuous improvement once the commercial manufacturing process is finalized and implemented.

The QbD approach is generally equated with Design of Experiments (DoE) and often seen only as a set of activities to characterize variable interaction and establish a design space in manufacturing processes. What is generally missed is the understanding that QbD is more holistic. It is a systematic methodology for designing quality into products that:

  • Begins with predefined objectives
  • Emphasizes product and process understanding and process control
  • Is based on sound science and quality risk management

In fact, this very language is codified into the ICH guidelines (see ICH Q8(R2)) such that the methodology of QbD is enshrined in the international regulatory framework. So, the question posed at the beginning of this section is a false one. It isn’t a question of whether or not to QbD, the question is how to do QbD.

QbD in the more holistic sense is considered a best practice for the entire product and process development lifecycle. The challenge has always been to meet the three requirements of QbD listed above in the absence of a structured, comprehensive knowledge management solution. The introduction of vertically-integrated knowledge management addresses this challenge definitively. The end result is the natural alignment of the development process with a holistic QbD strategy and ICH guidelines all underpinned by growing digital capabilities and maturity.

Process Understanding and Intelligence

The call to action going forward is “Know Where. Know How. Know Why.” It starts with always knowing where your information is located, presumably in a centralized source -of truth. Next, utilizing the information in a coordinated and collaborative manner to understand how it all comes together to demonstrate process control and the management of residual risk.

Vertically integrated knowledge management enables the aggregation and centralization of information within a structured repository creating this single source of truth. With all information centralized, this framework brings consistency, standardization, and shared access which then adds context and enables collaboration with this contextualized information. Layering in decision support tools combined with context starts the journey to more robust understanding as your knowledge base grows. As teams explore and characterize the evolving process from early development to production and CPV, a deeper understanding and intelligence emerges which can then be used to demonstrate robust process control and accelerate technology transfer activities digitally from one organization or one site to another.

Getting Agile

Agile methodologies have been commonly discussed over the past couple of decades and continue to receive significant attention as a recognized approach for improving the speed of product development and final product quality with lower risks and overall costs. This approach has been successfully deployed in the development of complex technology-based products ultimately transforming entire organizations.

More recently, there has been an increasing call for the deployment of agile methodologies in pharma and biotech R&D as a way to increase productivity and generate better outcomes. The term, Agile, can mean many things depending on the application, and this spectrum of definitions has generated a variety of implementation philosophies. However, there are some consistent themes that we can identify which support the application of agile to pharma R&D. Agile methodologies generally seek to:

  • Move the product development process closer to the customer
  • Focus the process on outcomes not features
  • Create small fit-for-purpose teams that can be flexible and move quickly
  • Empower teams to operate autonomously and iterate rapidly

Who is the “customer” in this context? Is it the patient? The manufacturing contractor? The regulators? In many cases, it is all of the above.

Do these principles fit with the regulatory requirements of pharma/biotech product development? Requirements-based knowledge management coupled with QbD/ICH workflows does move the process closer to each of the customer groups identified. An example is the philosophy of QbD where you “start with the end in mind”. More specifically, the end is the patient and you start your product development journey with an understanding of the patient needs via the Target Product Profile (TPP). Therefore, your knowledge management journey should begin with the TPP.

From the perspective of drug product quality, outcomes are defined as the attributes of the product that affect patient safety and efficacy. Again, the QbD/ICH process describes the need to identify the drug product attributes and to develop a clear understanding of how each attribute affects patient safety and efficacy. These attributes are ranked by risk and those attributes exceeding a specific threshold for risk are deemed as critical. From there the development program focuses on the manufacturing process to ensure that the product attributes deemed as critical meet the required specifications to ensure patient safety and efficacy.

The last two common elements of the agile methodology are operational paradigms where small, fit-for-purpose teams are established that can move quickly and operate autonomously.

These operational paradigms are not discussed in the QbD or ICH guidelines, but they are certainly relevant to improving the quality of outcomes. One example is a possible “team of teams” configuration where each team owns specific responsibilities which converge to cover the full set of development activities.

The McKinsey discussion (cited reference) of these themes also notes the need for a strong backbone of core processes, capabilities, and technologies to support agile operational modalities. Digital solutions for knowledge management constitute a critical “core capability and technology” which sit at the center of the agile teams’ activities providing access to a shared and evolving knowledge base. These teams can then work autonomously but still benefit from the aggregated and contextualized information generated by their activities to further support their activities and those of other teams throughout the lifecycle.

The agile approach enabled by vertically-integrated knowledge management improves R&D efficiency and, consequently, overall productivity by saving development costs, reducing cycle times, and increasing the probability of technical success.

Even marginal reductions in costs can yield a significant return on investment. Perhaps most importantly, this approach promotes the implementation of industry-recognized best practices and facilitates agile product development even within a highly regulated environment advancing organizations toward the goal of operational excellence.

In future KML whitepapers, we will continue to explore in more detail how vertically-integrated knowledge management supports the agile development journey for pharma/biotech R&D.

Laurent Lefebvre - Headshot

Laurent Lefebvre

RA CMC Director, Novartis

Laurent is the Director of RA GDD CMC at Novartis. With over 10 years of experience working as a worldwide Regulatory CMC Project Lead on blockbuster brands, he is an expert in the entire CMC product lifecycle in global regulatory environments. Laurent has been a core team member of the Novartis Regulatory Strategy and Intelligence for IDMP since 2014 and a member of the EFPIA ICH M4Q support team. He is involved in regular collaborations cross-industry (IDMP roundtables, Pistoia Alliance), digital initiatives (RIM structured authoring, master data & PLM), reviewer of the ISO IDMP guidelines and a Novartis contributor to regulatory intelligence discussions.
Laurent Lefebvre - Headshot

James Maxwell

Life Sciences Innovation Lead, Accenture

James Maxwell is an Innovation Lead at Accentures Global Centre for R&D and Innovation. He leads strategic innovation programs with global Life Sciences organizations to solve challenges, rapidly prototype and prove value for future solutions across the end-to-end Life Sciences value chain. With a background in design, research and innovation strategy he has worked with multiple organizations to take an innovation approach for solving challenges across CMC.
Paul Denny-Gouldson - Headshot

Paul Denny-Gouldson

CSO, Zifo

Paul is the CSO at Zifo RnD Solutions, a global specialist scientific and process informatics service provider working across research, development, manufacturing and clinical domains. He obtained his Ph.D. in Computational Biology from Essex University in 1996 and started his career as a Post Doc, and subsequently Senior Scientist at Sanofi-Synthelabo Toulouse (now Sanofi) for five years, where he managed a multidisciplinary molecular and cell biology department. He has also founded a number of companies focused on combining science, technology and business, and authored more than 25 scientific papers and book chapters.
Chris McCurdy

Chris McCurdy

Chief Architect of Healthcare and Life Sciences at Amazon Web Services

Chris McCurdy serves as Chief Architect of Healthcare and Life Sciences (HCLS) for Amazon Web Services (AWS), where he leads teams responsible for architecting cutting-edge services, unlocking data assets, and opening novel analytics capabilities for customers. With over 20 years of industry experience, Chris plays a key role in envisioning and developing innovative solutions and services that accelerate customer value while improving patient outcomes.
Isabell Hagemann Headshot - Digital CMC Basecamp - QbDVision

Isabell Hagemann

Scientific Assistant, Biological Development, Downstream, Bayer AG

Isabell Hagemann is a biochemical engineer by training and has worked at Bayer AG in the biological development downstream department in 2017. In that time, she has worked on process development, process characterization, and the technology transfers of several biologics using high-throughput development systems, modeling approaches, and knowledge management tools.

Ganga Kalidindi

Global Head TRD Data Assets & Insights, Novartis

As the Global Head TRD Data Assets and Insights at Novartis, Ganga Kalidindi brings a unique combination of Information Technology and Product Development expertise to delivering in a regulatory landscape. Throughout his career, he has striven to make direct positive impact on business providing leadership that creates cross-functional high-performing teams. Focusing on complex business and technical challenges, leading through change, and creating success that takes programs and companies to a winning status.
Fran Leira Headshot - Digital CMC Basecamp - QbDVision

Fran Leira

Global Head of Process Engineering CoE, CSL Behring

Fran Leira is a biopharma Professional with over 20 years of experience in QC, MSAT/Tech Ops at companies like Genentech, GSK, Merck, and Lonza where he supported Product and Process Lifecycle Management at site-based and global roles. He is currently the Global Head of Process Engineering CoE at CSL Behring.

Florian Aupert Headshot - Digital CMC Basecamp - QbDVision

Florian Aupert

Lab Head, Biological Development, Bayer AG

Florian has a B. Sc. and M. Sc. in pharmaceutical biotechnology with a focus on bioprocess engineering. Since 2018, he’s worked at Bayer AG in Biological Development, concentrating on portfolio program management and tech transfer.

Devendra Deshmukh

Global Head, Digital Science Business Operations, Thermo Fisher Scientific

Devendra Deshmukh currently leads Global Business Operations for Digital Science Solutions at Thermo Fisher Scientific. In this role he oversees operations broadly for the business across its product portfolio and leads the global professional services, technical support, and product education teams.

Mark Fish

Managing Director, Scientific Informatics, Accenture

Mark Fish is Managing Director and Global Lead for Accenture’s Scientific Informatics Services Business. Mark has over 25 years of experience in leadership roles in Accenture, Brooks Life Sciences and Thermo Fisher Scientific delivering innovative solutions to the pharmaceutical sector and is passionate about drug discovery and development, translation research and manufacturing transformation. Mark has extensive experience in agile software development, data strategy, process engineering and robotic automation for research, analytical development and quality control in Life Sciences.

Chris Puzzo

Solution Architect, Digital & Data, Zaether

Chris is a Solution Architect with Zaether, focusing on delivering next-generation digital and data solutions for GxP Life Sciences customers. Chris has previously held technical operations roles within multiple gene therapy manufacturers, including Thermo Fisher Scientific’s CDMO organization where he supported various capital projects including the design, build, and startup of new GxP manufacturing capacity.

Victor Goetz, Ph.D

Executive Director, TS/MS New Modalities and Data Strategy, Eli Lilly and Company

Victor Goetz, Ph.D. is the Executive Director of Technical Services New Modalities and Data Strategy at Eli Lilly and Company. He has over 35 years of industry experience in developing and commercializing nine novel medicines to enhance the exchange of knowledge needed to speed the delivery of new medicines to patients. Dr. Goetz holds a BS in chemical engineering from Stanford University and a PhD in chemical and biochemical engineering from the University of Pennsylvania.

Rachelle Howard

Director of Manufacturing Systems Automation and Digital Strategy, Vertex Pharmaceuticals

Rachelle is the Director of Manufacturing Systems Automation and Digital Strategy for Vertex’s Small Molecule Manufacturing Center. She oversees the site Automation Engineering function and has co-led Vertex’s global Digital Manufacturing Transformation program since 2019. She leads several initiatives related to data integrity, data management, and employee education. Rachelle is a graduate of Tufts University and the University of Connecticut where she has degrees in Chemical Engineering and a PhD in Process Control.

Vijay Raju

Vice President, CMC Management, Flagship Pioneering

Vijay currently leads CMC activities to deliver on Pioneering Medicines portfolio. The portfolio is built on Flagship Pioneering’s bio-platforms covering multiple modalities (small molecules, biologics, cell & gene therapies). Vijay was previously in technical leadership roles at Novartis.

Greg Troiano

Head of cGMP Strategic Supply & Operations, mRNA Center of Excellence, Sanofi

Greg serves as Head of cGMP Strategic Supply and Operations at the mRNA Center of Excellence at Sanofi, where he is responsible for all aspects of clinical production and raw material supply chain. He joined Sanofi via acquisition of Translate Bio, where he was Chief Manufacturing Officer and responsible for Technical Operations. Over his 20+ year career in the drug delivery field, Greg had various roles leading the pharmaceutical development of complex formulations, including numerous nano- and microparticle based systems. Greg received his MSE and BS in Biomedical Engineering from The Johns Hopkins University and was elected and inducted into the American Institute for Medical and Biological Engineering (AIMBE) College of Fellows in 2020 for recognition of his accomplishments in drug delivery.

Pat Sacco

Senior Vice President Manufacturing, Quality, and Operations, SalioGen

Pat is a Biotechnology technical operations executive with 30+ years of experience leading and managing technical operations functions at numerous innovative companies in the biotech and life sciences industries. He has a passion for advancing and implementing best practices in pharmaceutical manufacturing.

Diana Bowley

Associate Director, Data & Digital Strategy, AbbVie

Diana is the Associate Director, Data & Digital Strategy in S&T-Biologics Development and Launch leading the organization’s Digital Transformation since October 2021. She joined AbbVie in 2012 in the R&D-Discovery Biologics group focused on antibody and multi-specific protein screening and engineering, leading multiple programs to the cell line development stage. In 2017 she joined Information Research and led a team of IT professionals who supported AbbVie’s Discovery Scientists in Biotherapeutics, Chemistry, Immunology and Neuroscience. She has a PhD in Molecular Biology from The Scripps Research Institute and Bachelor of Science in Chemistry from The University of Northern Iowa.

Robert Dimitri, M.S., M.B.A.

Director Digital Quality Systems, Thermo Fisher Scientific

Robert Dimitri is a Director of Digital Quality Systems in Thermofisher’s Pharma Services Group. Previously he was a Digital Transformation and Innovation Lead in Takeda’s Business Excellence for the Biologics Operating Unit while leading Digital and Data Sciences groups in Manufacturing Sciences at Takeda’s Massachusetts Biologics Site.

Devendra Deshmukh

Global Head, Digital Science Business Operations, Thermo Fisher Scientific

Devendra Deshmukh currently leads Global Business Operations for Digital Science Solutions at Thermo Fisher Scientific. In this role he oversees operations broadly for the business across its product portfolio and leads the global professional services, technical support, and product education teams.

Grant Henderson

Sr. Dir. Manufacturing Science and Technology, VernalBio

Grant Henderson is the Senior Director of Manufacturing Science and Technology at Vernal Biosciences. He has years of expertise in pharmaceutical manufacturing process development/characterization, advanced design of experiments, and principles of operational excellence.

Ryan Nielsen

Life Sciences Global Sales Director, Rockwell Automation

Ryan Nielsen is the Life Sciences Global Sales Director at Rockwell Automation. He has over 17 years of industry experience and a passion for collaboration in solving complex problems and adding value to the life sciences space.

Shameek Ray

Head of Quality Manufacturing Informatics, Zifo

Shameek Ray is the Head of Quality Manufacturing Informatics and Zifo and has extensive experience in implementing laboratory informatics and automation for life sciences, forensics, consumer goods, chemicals, food and beverage, and crop science industries. With his background in services, consulting, and product management, he has helped numerous labs embark on their digital transformation journey.

Max Peterson​

Lab Data Automation Practice Manager, Zifo

Max Petersen is the Lab Data Automation Practice Manager at Zifo responsible for developing strategy for their Lab Data Automation Solution (LDAS) offerings. He has over 20 years of experience in informatics and simulation technologies in life sciences, chemicals, and materials applications.

Michael Stapleton

Board Director, QbDVision

Michael Stapleton is a life sciences leader with success spanning leadership roles in software, consumables, instruments, services, consulting, and pharmaceuticals. He is a constant innovator, optimist, influencer, and digital thought leader identifying the next strategic challenge in life sciences, executing and operationalizing on high impact strategic plans to drive growth.

Matthew Schulze

Head of Digital Pioneering Medicines & Regulatory Systems, Flagship Pioneering

Matt Schulze is a Senior Director in the Flagship Digital, IT, and Informatics team, where he leads and manages the digital evolution for Pioneering Medicines. His role is pivotal in ensuring that digital strategies align with the overall goals and objectives of the Flagship Pioneering initiative.

His robust background in digital life sciences includes expertise in applications, informatics, data management, and IT/OT management. He previously spearheaded Digital Biomanufacturing Applications at Resilience, a CDMO start-up backed by Arch, where he established a team responsible for implementing global manufacturing automation systems, Quality Assurance applications, laboratory systems, and data management applications.

Matt holds a B.S. in Biology and Biotechnology from Worcester Polytechnic Institute and an M.B.A. from the Boston University Questrom School of Business, where he focused on Strategy and Innovation.

Daniel R. Matlis

Founder and President, Axendia

Daniel R. Matlis is the Founder and President of Axendia, an analyst firm providing trusted advice to life science executives on business, technology, and regulatory issues. He has three decades of industry experience spanning all life science and is an active contributor to FDA’s Case for Quality Initiative. Dan is also a member of the FDA’s advisory council on modeling, simulation, and in-silico clinical trials and co-chaired the Product Quality Outcomes Analytics initiative with agency officials.

Kir Henrici

CEO, The Henrici Group

Kir is a life science consultant working domestically and internationally for over 12 years in support of quality and compliance for pharma and biotech. Her deep belief in adopting digital technology and data analytics as the foundation for business excellence and life science innovation has made her a key member of PDA and ISPE – she currently serves on the PDA Regulatory Affairs/Quality Advisory Board

Oliver Hesse

VP & Head of Biotech Data Science & Digitalization, Bayer Pharmaceuticals

Oliver Hesse is the current VP & Head of Biotech Data Science & Digitalization for Bayer, based in Berkeley, California. He has a degree in Biotechnology from TU Berlin and started his career in a Biotech start-up in Germany before joining Bayer in 2008 to work on automation, digitalization, and the application of data science in the biopharmaceutical industry.

John Maguire

Director of Manufacturing Sciences, Sanofi mRNA Center of Excellence

With over 18 years of process engineering experience, John is an expert in the application of process engineering and operational technology in support of the production of life science therapeutics. His work includes plant capability analysis, functional specification development, and the start-up of drug substance manufacturing facilities in Ireland and the United States.

Chris Kopinski

Business Development Executive, Life Sciences and Healthcare at AWS

As a Business Development Executive at Amazon Web Services, Chris leads teams focused on tackling customer problems through digital transformation. This experience includes leading business process intelligence and data science programs within the global technology organizations and improving outcomes through data-driven development practices.

Tim Adkins

Digital Life Science Operations, ZÆTHER

Tim Adkins is a Director of Digital Life Sciences Operations at ZÆTHER, serving the life science industry by assisting companies reach their desired business outcomes through digital IT/OT solutions. He has 30 years of industry experience as an IT/OT leader in global operational improvements and support, manufacturing system design, and implementation programs.

Blake Hotz

Manufacturing Sciences Data Manager, Sanofi

At Sanofi’s mRNA Center of Excellence, Blake Hotz focuses on developing data ingestion and cleaning workflows using digital tools. He has over 5 years of experience in biotech and holds degrees in Chemical Engineering (B.S.) and Biomedical Engineering (M.S.) from Tufts University.

Anthony DeBiase

Offering Manager, Rockwell Automation

Anthony has over 14 years of experience in the life science industry focusing on process development, operational technology (OT) implementation, technology transfer, CMC and cGMP manufacturing in biologics, cell therapies, and regenerative medicine.

Andy Zheng

Data Solution Architect, ZÆTHER

Andy Zheng is a Data Solution Architect at ZÆTHER who strives to grow and develop cutting-edge solutions in industrial automation and life science. His years of experience within the software automation field focused on bringing innovative solutions to customers which improve process efficiency.

Sue Plant

Phorum Director, Regulatory CMC, Biophorum

Sue Plant is the Phorum Director of Regulatory CMC at BioPhorum, a leading network of biopharmaceutical organizations that aims to connect, collaborate, and accelerate innovation. With over 20 years of experience in life sciences, regulatory, and technology, she focuses on improving access to medicines through innovation in the regulatory ecosystem.

Yash Sabharwal​

President & CEO, QbDVision

Yash Sabharwal is an accomplished inventor, entrepreneur, and executive specializing in the funding and growth of early-stage technology companies focused on life science applications. He has started 3 companies and successfully exited his last two, bringing a wealth of strategic and tactical experience to the team.

Joschka Buyel

Director of Product Management, QbDVision

Joschka Buyel is the Director of Product Management at QbDVision. He was previously responsible for the rollout and integration of QbDVision at Bayer and worked on various late-stage projects as a Quality-by-Design Expert for Product & Process Characterization, Process Validation, and Transfers. Joschka has a Ph.D. in Drug Sciences from Bonn University and a M.S. and B.S. in Molecular and Applied Biotechnology from the RWTH University.

Luke Guerrero

COO, QbDVision

A veteran technologist and company leader with a global CV, Luke currently oversees the core business operations across QbDVision and its teams. Before joining QbDVision, he developed, grew, and led key practices for international agency Brand Networks, and spent six years deploying technology and business strategies for PricewaterhouseCoopers’ CIO Advisory consulting unit.

Gloria Gadea Lopez

Head of Global Consultancy, Business Platforms | Ph.D., Biosystems Engineering

Gloria Gadea-Lopez is the Head of Global Consultancy at Business Platforms. Using her prior extensive experience in the biopharmaceutical industry, she supports companies in developing strategies and delivering digital systems for successful operations. She holds degrees in Chemical Engineering, Food Science (M.S.), and Biosystems Engineering (Ph.D.)

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