TetraScience Ideal Buyer Personas 2024 PDF

TetraScience Ideal Buyer Personas 5-2024 Ideal Key Personas Chief Data Officer / AI Officer Buyer Head of Research Personas Head of Development / CMC Head of QC / Quality Chief Information Officer...

TetraScience Ideal Buyer Personas 5-2024 Ideal Key Personas Chief Data Officer / AI Officer Buyer Head of Research Personas Head of Development / CMC Head of QC / Quality Chief Information Officer Head of Scientific IT Scientific IT (Data Engineers, Data Architects) Confidential Presentation | © 2024 TetraScience, Inc. 2 Chief Data Officer (CDO) Role in purchase process Job Titles Budget holder / economic buyer Chief Data (and Artificial Intelligence) Officer Chief Data Innovation Officer Chief Analytics Officer Head of Insights and Analytics “Changing the culture and demonstrating value is the biggest challenge for chief data Head of Business Intelligence officers to keep their jobs.” Head of Data Science (and Data Management) Head of Data and ML Platforms Head of Computational Chemistry Background Responsibilities Is a data / business leader Is typically the economic buyer with purchase and Manage the organization's data and analytics operations budget authorization Drive use and governance of data across the organization Understands how data science contributes to the Set the data strategy bottom line and business strategy Deliver timely data-related insights for security issues and Wants to increase efficiency and productivity, reduce business process optimization costs and risks, and drive innovation Drive framework development and control policies Focused on the business value of the solution Bring together data silos across business domains Driven by a need for the company to deliver better Foster a data-driven culture drugs faster through better and faster insights Confidential Presentation | © 2024 TetraScience, Inc. 3 Chief Data Officer (CDO) Goals Discovery Questions Align data strategy with business objectives What is your company’s data strategy? What are your biggest inefficiencies in data management? Optimize business support with data insights How do you scale your data management solutions? Ensure data readiness (available and usable) and that How much time do your teams spend finding, extracting, the organization gets most out of it cleaning, and processing data to make it AI-ready? Demonstrate the value of data as a corporate asset How do you ensure and measure business value from Remove process bottlenecks related to data workflows scientific data? Optimize productivity while avoiding risks and cost What do you do to minimize risks associated with data? Ensure data security What is your data maturity / AI readiness index score? Challenges Key Messages Inefficient and ineffective data management Improve your scientific data management approach with a partner that has deep expertise in centralizing, managing and Integrate business and data silos transforming scientific data. Multiple versions of the truth inside organizations Reduce your efforts in preparing data for scientific AI with an Scale data management according to changing automated, purpose-built, and secure cloud-based solution. requirements Lack of access to AI-ready data to support decision making Make your Scientific AI projects successful with large-scale, AI-native scientific datasets engineered by TetraScience. Identify safety issues and risks Build a case for change and manage that change Be confident about the outcomes of your AI algorithms collaborating with a long-term expert in scientific data. Measure success as link between data and outcomes is indirect Identify the most impactful use cases for Scientific AI with Tetra experts in science, data, AI, and business outcomes (Sciborgs). Confidential Presentation | © 2024 TetraScience, Inc. 4 Head of Research Role in purchase process Job Titles Budget holder /influencer Head / ESVP / SVP / VP of Research / Discovery Head of R&D / Research and (Early) Development Chief Scientific Officer “The onus is on pharma and biotech to become more efficient Head of Biologics / Oncology / Vaccines / Translational Research and reduce costs by the adoption Competence Center: of new technologies and ideas.” High Throughput Screening / Bioprocessing / C&GT / NGS (Next Justin Bryans, Chief Scientific Officer, Charles River Laboratories Generation Sequencing) / Biotechnology Background Responsibilities Often economic buyer and final decision maker Identify and prioritize opportunities for new therapeutic areas and target indications for research focus (e.g. for new disease areas/targets) for purchase; sometimes strong influencer Establish IP with a defined number of new molecules delivered to development Understands the organization and how science, Optimize productivity and innovation power of research IT, and data science affect research Define vision and roadmaps to solve scientific problems Wants to drive innovation, increase efficiency Manage budgets and deliver financial analysis and productivity, reduce costs in research Overview of scientific data and knowledge generated in discovery and research Wants to “fail early and fail cheap” Interface with key stakeholders of other departments and partners (e.g., CROs) Deliver research projects on time and on budget Is driven by delivering treatments to clinic faster Allocate resources (e.g. personnel, equipment) across research projects Is focused on the business value of a solution Leverage innovative technologies and scientific know-how to accelerate and optimize research outcomes Confidential Presentation | © 2024 TetraScience, Inc. 5 Head of Research Goals Discovery Questions Discover disease targets and novel therapeutics faster What are your biggest obstacles to accelerating time to clinic? and at a lower cost to clinic How are you use your scientific data to innovate? Drive and accelerate product innovation What is your level of readiness to use AI and in silico methods for Ensure that the scientific strategy and portfolio discovery? supports business and financial objectives What are the costs and time related to wet lab experiments? Manage partnerships with CROs and academics How are you managing your scientific data and knowledge today? Manage research as a business Where do you see opportunities of improvement for research Proactively embrace scientific challenges identifying productivity and efficiency? novel drug candidates How are you collaborating with other departments like early Attract and retain scientific talent and build high development and partners like CROs? performance teams Challenges Key Messages Innovate novel blockbuster therapies Protect and access your data and scientific IP in a secure, Identify and optimize new lead candidates cloud-based environment through automated data centralization Cost pressure due to flat or declining budgets Optimize data workflows with proven and impactful scientific use Keep pace with new technologies and assessing their value cases. Manage data from collaborations (CROs, academics etc.) Compare harmonized, vendor-agnostic data for scientific insights Inefficient and ineffective data & knowledge management Leverage AI for decision-making in discovery and research Build the foundation for Scientific AI with AI-native scientific for their daily business datasets, purpose-engineered for science and AI. Assess and mitigate IP risks while fostering innovation Easily exchange liquid data between and among biopharmas, CROs, Determine which projects to pursue, maintain, or cancel and scientific vendors, fueling collaborative innovation. Confidential Presentation | © 2024 TetraScience, Inc. 6 Head of Development / CMC Role in purchase process Job Titles Budget holder /influencer Head / ESVP / SVP / VP of R&D / (Bioprocess) Development / Formulations / Process Development / CMC / Tech Transfer Head of R&D / Research & (Early) Development “The onus is on pharma and Head of Development & Manufacturing / Analytical Development & QC biotech to become more efficient Chief Scientific Officer and reduce costs by the adoption Therapeutics Area: of new technologies and ideas.” Development Unit Oncology / Vaccines / Targeted Therapies Justin Bryans, Chief Scientific Officer, Charles River Laboratories Responsibilities Background Develop and optimize the production and quality testing of drug substances, drug Often economic buyer and final decision maker for product intermediates, and drug products for QC/manufacturing purchase; sometimes strong influencer Optimize and scale up therapeutics formulations and recipes Understands the organization and how science, IT, and Transfer and support analytical test methods for QC/manufacturing data science affect drug development Manage budgets and deliver financial analysis Wants to increase efficiency and productivity, reduce Overview of scientific data and knowledge generated in development costs and risks in drug development Interface with key stakeholders of other departments and partners (e.g., CDMOs) Is driven by the need of the company to deliver better Deliver formulation projects on time and on budget treatments to the market faster Allocate resources (e.g. personnel, equipment) across development programs Is focused on the business value of a solution Establish operational policies for new testing methods and align with regulations implemented Oversee and manage the entire drug development portfolio, from preclinical Needs to collaborate with different stakeholders for studies through regulatory submissions and approvals tech transfer Evaluate and prioritize drug candidates in preclinical and clinical development Confidential Presentation | © 2024 TetraScience, Inc. 7 Head of Development / CMC Goals Discovery Questions Develop and bring novel therapeutics to market faster What are your biggest obstacles to advancing new drug candidates to and at a lower cost clinic? Drive and accelerate product testing and formulation How are you leveraging your scientific data to optimize formulations and Manage development as a business processes regarding stability, safety, quality, and yield? Proactively embrace scientific challenges in formulation How do you keep up with regulatory changes around electronic filings? and scale-up Where do you see opportunities of improvement for productivity and Attract and retain scientific talent and build high efficiency in development? performance teams What is your level of readiness to support AI for drug development? Build and maintain a robust development pipeline How are you managing your scientific data and knowledge today? What are your costs related to tech transfer? Challenges How are you collaborating with other departments like quality control Minimize costs and maximize operational productivity and partners like CDMOs? Optimize formulations and manufacturing processes to maximize therapeutics stability, yield, quality, and safety Key Messages Cost pressure due to flat or declining budgets Protect and access your data and scientific IP in a secure, cloud-based Keep pace with new technologies and assessing their value environment through automated data centralization Balance quality, compliance, efficiency, and speed Optimize data workflows with proven and impactful scientific use cases. Collaborate with partners (CDMOs) Compare harmonized, vendor-agnostic data for scientific insights Inefficient and ineffective data and knowledge management Build the foundation for Scientific AI with AI-native scientific datasets, Make faster decisions leveraging all data in development purpose-engineered for science and AI. Leverage AI for decision-making in development due to the Easily exchange liquid data between and among biopharmas, CDMOs, rapid growth of data and scientific vendors, fueling collaborative innovation. Confidential Presentation | © 2024 TetraScience, Inc. 8 Head of QC/Quality Role in purchase process Job Titles Budget holder /influencer Head of Quality / Quality Control / Quality Unit Head of Global Quality / Quality & GxP Compliance Head of Quality & Regulatory / Quality & Pharmacovigilance “The challenges for a regulatory Head of Manufacturing / Manufacturing Operations /Operations professional shift more and more Head of Regulatory Affairs / Science / Compliance / Information / to strategic decision-making and Strategy shaping the regulatory landscape.” Global Digital Transformation Leader Quality Background Responsibilities Drives or influences purchase decisions that are Provide strategic regulatory and quality guidance relevant for quality and the regulated space Mitigate all quality and regulatory related risks Trusts vendors who understand the handling of Oversee Quality Control (QC) / all regulatory / quality matters and data and data workflows in the regulated space (internal and external) compliance-related activities (use the right jargon!) Ensure the organization is compliant with regulations like GxP etc. Interested in solutions that reduce quality and compliance efforts, minimize risks, and support Ensure product quality (compliance with specifications) and safety audits (e.g., purity, dosing) and its documentation Interested in solutions that speed batch release Support and maintain the quality management system (QMS), the Needs a single source of truth of data and data electronic document management system (EDMS) and other integrity / traceability electronic systems related to the QMS Risk averse and likes to see proof of claims Oversee internal and external audits as well as (major) investigations Confidential Presentation | © 2024 TetraScience, Inc. 9 Head of QC/Quality Goals Discovery Questions Ensure company-wide regulatory and quality How do you ensure the integrity and traceability of scientific data compliance (incl. product specifications) used for decisions in the regulated space? Ensure drug product safety How do you ensure fast yet reliant product / batch release? How do you minimize the compliance efforts in development and Minimize product release times and inventory quality data workflows? Minimize quality and regulatory risk and events What is the validation effort for your scientific data workflows? Minimize compliance efforts and costs What is the effort of compiling data for reports and dossiers? Promote a culture of quality Are you considering AI to optimize quality and support compliance? Challenges Key Messages Compliance with large variety of global regulations Eliminate the source of human errors with a data-centric solution Compliance with product specs at increasing that automates the collection, centralization and harmonization of number of product/ market combinations scientific data. High validation and compliance-related efforts Reduce your validation efforts with productized, validated that are considered non-value adding and costly integrations to instruments, informatics and data applications as well Uncertainty about data integrity and traceability as with a GxP package that includes a Verification & Validation document set. Ensuring product safety and efficacy with Be confident about the integrity and traceability of your scientific scattered data data with a solution that is designed to support all ALCOA++ Timely product / batch release with siloed systems principles as well as 21 CFR Part 11, Annex 11, and GxP. High efforts creating documents, reports, and Minimize audit efforts with a partner maintains a rigorous quality dossiers due to scattered data organization and lives a core culture of compliance. Confidential Presentation | © 2024 TetraScience, Inc. 10 Chief Information Officer (CIO) Role in purchase process Job Titles Budget holder / economic buyer Chief Information (and Digital) Officer (CIO) Chief Technology Officer (CTO) Chief Digital Officer (CDO) “As their jobs evolve and require Head of Enterprise Architecture disparate skill sets, CIOs must be flexible.” Head of Scientific Platforms Head of Information Technology / IT Operations Background Responsibilities Is an IT / business leader Oversee company’s digital strategy Is typically the economic buyer with purchase and Manage IT profitability for the organization to grow top and budget authorization bottom lines Understands the organization and how IT contributes Optimize the organization’s productivity and process to the bottom line and business strategy efficiency through suitable IT deployments Wants to increase efficiency and productivity, reduce Manage digital transformation initiatives costs and risks, and drive innovation Fund critical technology innovation with the highest ROI Focused on the business value of the solution Identify new digital technologies & investments Driven by a need for the company to deliver better Run information services and systems architecture drugs faster Maintain relationships with strategic technology vendors Confidential Presentation | © 2024 TetraScience, Inc. 11 Chief Information Officer (CIO) Goals Discovery Questions Minimize IT costs through lower CapEx, OpEx, maintenance, What is your company’s IT strategy? and support costs How do you manage the costs for your diverse scientific Optimize business support informatics landscape? Remove process bottlenecks What are your biggest areas of process inefficiency? Optimize productivity while avoiding risks and cost What are your plans to digitally transform your labs? Reduce and simplify technology platforms across the business How do you manage change with your scientific Identify transformative technology to boost business results instrument and software vendors? Ensure IP security How do you minimize security and compliance risks? Key Messages Challenges Be confident about the security and and integrity of your IT investments without clear ROI scientific data with a single, centralized, and trusted Costs of legacy technologies and applications cloud-based platform and robust, industrialized, and Inefficiencies due to multiple, disparate systems validated integrations. Complex, customized systems Build a future-proof foundation for AI while satisfying your High cost of re-work current needs for connectivity and automation. Projects being over budget and delayed impact revenue Support Scientific AI initiatives with the world’s only AI-native Low operational efficiency scientific datasets (Tetra Data). Inability to scale technology Optimize your deployments with a partner that provides you Lost or compromised IP with industry best practices and a team of experts with a Adapt to constantly changing business requirements unique combination of skills (science, data, AI & business (e.g., through M&As) and developing technology outcomes). Confidential Presentation | © 2024 TetraScience, Inc. 12 Head of Scientific IT Role in purchase process Job Titles Decision maker Head of Scientific IT / Scientific Informatics / Scientific Computing Head of Discovery / R&D / Development / QC / Manufacturing IT " As digital transformation projects accelerate Head of Digital / Digitalization in R&D / Digital Solutions and increase in scope, demonstrating a Head of Technology – Scientific IT compelling ROI is vital to earning support and Head of Lab Informatics / Lab Automation funding for additional digital initiatives.” Head of Digital Transformation (R&D, QC) Background IT leader for a specific scientific area (Discovery, Responsibilities Research, Development, QC, Manufacturing) Manage scientific and/or lab IT Is typically the final decision maker Drive a cloud-based, digital, and data-driven IT environment Provide scientists and data scientists (their internal Often drives the evaluation customers) with suitable technology to optimize their Considers ROI and IT budget productivity and scientific outcomes Values vendors with pharma experience Ensure optimal setup and configuration of systems Selects solutions based on scientific and business needs Support scientists’ and data scientists’ data needs Might be concerned about additional workload through Ensure system health and data security the new solution Keep scientific IT systems updated Needs to see the value-add of solutions above existing Make purchases that maximize ROI for science systems Drive purchase pricing and timing of the implementation Confidential Presentation | © 2024 TetraScience, Inc. 13 Head of Scientific IT Goals Discovery Questions Configure IT landscape to optimize scientific productivity What are your biggest IT challenges supporting your scientists Ensure teams’ ability to reuse scientific data for and data scientists? analytics- and AI-enabled decision making Where you are with the implementation of your digital Optimize IT costs including maintenance and support transformation initiatives? Ensure system security and IT regulatory compliance How do handle fragmented, siloed experimental data today? Ensure future-proof data- / IT-environment for science How many different lab instruments, applications, and processes do you support? How do you ensure AI-readiness of data? Challenges What are your biggest challenges ensuring security and Effort to provide scientists and data scientists with the regulatory data compliance of data? data they need from different siloed data sources What are your plans to modernize/digitalize labs? A scattered and complex landscape of scientific IT Key Messages systems leading to high integration efforts Enable analytics- and AI-driven decisions with a purpose-built solution for Lack of data standards across vendors, instruments scientific data workflows. and applications Build a future-proof foundation for Scientific AI with large-scale, liquid, Delivering on the expectation of scientists to leverage purpose-engineered, and compliant Tetra Data while satisfying your needs for connectivity and automation. Minimize your data preparation efforts their data for advanced analytics and AI with a data-centric solution that automatically collects, centralizes and Complexity managing IT, implementing governance, transforms scientific data. and maintaining data history Ensure the success of your company’s Scientific AI initiatives with the Highly regulated environments slowing down world’s only provider of AI-native scientific datasets. implementation times Maximize the success of your projects through the support by experts in Finding opportunities for costs savings science, data, AI and business outcomes (Tetra Sciborgs). Confidential Presentation | © 2024 TetraScience, Inc. 14 Scientific IT (Data Engineers, Data Architects) Role in purchase process Job Titles Primary user / influencer Data (& Knowledge) Engineer, Systems Engineer, Integration Engineer, Research Data Engineer (Lead / Senior / Enterprise) Data Architect, (Business) Solutions Architect " Top challenges are data integration, Data Architect Bioprocess / Pharma Process processing, and governance.” Scientific Computing Specialist Director Informatics Background Responsibilities Primary user and typically involved in the buying End-to-end process providing scientists and data scientists with decision reliable, clean, centralized, harmonized, FAIR and AI-ready data Builds solutions for end users, including scientists Partner with scientists and data scientists to bridge science and and data scientists technology Determines data processing and management Integrate lab instruments and applications requirements Build pipelines to process and enrich scientific data Trusts vendors who understand scientific data Automate manual data collection and preparation formats, instruments, and applications Provide the ability to easily search and access scientific data (e.g., Has a deep understanding of technology and data through applications typically used in workflows like ELN / LIMS) Is focused on the needs of their scientists and Create dashboards to show status of instruments and processes data scientists and how they can use data (e.g., Set up and configure systems for analytics and AI) Troubleshoot and resolve data- / IT-related problems Confidential Presentation | © 2024 TetraScience, Inc. FAIR = findable, accessible, interoperable, reusable 15 Scientific IT (Data Engineers, Data Architects) Goals Discovery Questions Minimize time and cost to integrate and maintain new How much time do you spend developing and maintaining instruments and applications point-to-point integrations of instruments, informatics Enable data to flow between instruments and applications, and sensors? informatics applications With how many different instruments and applications do you Provide their internal customers, scientists and data use and how many different data formats do you have? scientists, with access to data wherever needed How easy is it to create and maintain data pipelines? Enable the reuse of FAIR scientific data How are scientists and data scientists accessing data today? How do you ensure your scientific data is FAIR? Challenges How do you define and build scientific data workflows today? Growing complexity due to increasing number of How do you prepare scientific data for analytics and AI/ML? instruments and applications Accessing multiple siloed systems to locate, extract, Key Messages compile data Minimize data preparation efforts with a data-centric solution that Different incompatible data formats across vendors automatically collects, centralizes and transforms data. Manually collecting, moving and processing of data, The Tetra Scientific Data and AI Cloud is purpose-built for scientific which is slow and error prone data workflows. Point-to-point, DIY integrations require significant Ensure high data quality and reusability with Tetra Data, which is development and maintenance effort large-scale, liquid, compliant, well-engineered, and FAIR and enables advanced analytics and AI. Keeping up with new technologies and new product Focus your work on high impact with industry best practices and versions with the support of a team with combined expertise in science, Providing FAIR and analytics- / AI-ready is hard data and AI that focuses on business outcomes. Confidential Presentation | © 2024 TetraScience, Inc. 16