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An Introduction to MES and Its Importance to the Precision Therapeutics Value Chain

by Kevin McMahon | posted on December 19, 2022

Precision Therapeutics as a New Class of Biologics

Precision therapeutics refers to the new classes of treatments that have been developed to treat diseases with specific characteristics, whether it be genetic defects, immunological deficiencies, or molecular profiles. Examples of precision therapeutics include but are not limited to the following:

  • Gene Therapythe transfer of genetic material (RNA or DNA) into the cells of a patient’s body either through extracted cells to reintroduce or directly using viral vectors or lipid nanoparticles to carry to the disease causing area.
  • CAR-T and CAR-NKChimeric Antigen Receptors (CAR) is the addition of specific proteins on the surface of native or donor immune cells to create targeted responses to cancer or disease generating cells in a patient’s body.
  • Neogenomic Vaccinesspecific to an antigen produced in the microbiome of the diseased cells and used to identify and flag these mutated or diseased cells for destruction.
  • Viral vector and plasmid productionusing CRISPR/Cas9 to create plasmids encoding desired protein antigens, the plasmid can be delivered using viral vectors like AAV or lipids to deliver to cells in-vivo or ex-Vivo. 
  • CRISPR/Cas9 – CRISPR can be used as a tool to edit the base pairs of genes and CAS9 acts as a genetic scissors to cut genes in a specific region where deletion, disruption and correction are required.
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Bioprocess Design of Precision Therapeutics

Bioprocess design has become a well-structured and documented methodology for traditional biologics such as monoclonal antibodies. A typical design approach will use standard process templates to perform design of experiments for process characterization and identification of CPPs and CQAs through failure modes and effects strategies. In this design approach, process variability commonly falls within the accuracy tolerance of analytical control methods used to evaluate products – hence the terminology “well characterized” biologics. 

With the arrival of novel gene, cell and tissue therapies, a different type of processing is introduced in which the variation in processing outcomes is less “testable”.  Multiple process and analytical measurements are real-time used to choose what process path to follow, almost a choose your own story.  The QC method becomes part of the process and potency measurements will often involve the same product manipulation techniques as the manufacturing process (cell expansion, infection).  For process design, it can seem virtually impossible to repeat the same process more than once and one ends with a multiplicity of related but non-identical processes and QC results.  In this situation, we are pushed beyond the traditional “process is the product” paradigm into a new realm where the “data is the product”.

 

Manufacturing with Data Intelligence 

A Manufacturing Execution System, or MES, is a digital solution used in manufacturing or production of life science products that replaces paper-based documentation to digitally execute manufacturing processes and capture a record of the who, what and when of the entire production process from raw materials to intermediate or finished goods. It is an integral part of any manufacturing operations management (MOM) in the life sciences and a keystone of a digital manufacturing 4.0 plan overall.

Step one is digitalizing and contextualizing your data and process, and MES is the keystone to achieving this. The therapeutics industry also generates massive amounts of data and this needs to be stored and curated in a format that makes it accessible and interrogatable at all levels of the value chain. MES as part of a MOM application suite extends the MES capabilities as a unified platform, to manage the inputs (Schedule, Materials, Assets, Personnel) and the outputs (Product, Intermediates, Samples, Data and documentation).

MES as part of a manufacturing operations management application suite can intensely improve the following pain points in manufacturing precision therapeutics:

 

  PROBLEM SOLUTION
1 Make-to-order product and speed of delivery Streamline through Automation of process and data with an MES
2 Right first time, every time – Speeding up delivery of treatments to patients Quality by design – MES provides inline checks and guardrails to ensure correct materials, recipes, expirations, parameters, samples, and procedures are taken and followed throughout the process.
3 Regulatory and compliance – Manufacturing in a CGMP environment to produce products requires adherence to established FDA and regulatory body requirements and standards for IT infrastructure The right MES system can build-in compliance and rules across the process and provide the infrastructure and toolset to apply requirements for every batch and product. Create inline checks that follow all your supporting GMP documentation and ensure robust production processes with proper oversight and governance. MES provides audit trails of all actions taken in the system and connects directly to primary sources of data to capture accurate, time-stamped, attributed data. MES provides 21 CFR part 11 compliance controls with data integrity and e-signatures to restrict performers and verifiers to trained personnel.
4 Talent pool is small and expensive- tied up with review cycles for paper-based batch records or investigations of deviations Review by exception and inline checks and controls allows a redeployment of valuable staff to value add activities like manufacturing, dispositioning, continuous improvement.
5 Scalability of products and processes Agile build and deploy of MES, must allow composability to cater to many customers, speed up tech-transfer from development to production, reuse and repurpose validated blocks of executable processes.
6 Chain of Identity (COI) and chain of custody (COC) across entire value chain Reduce documentation and spreadsheets to track COC and COI of your specimens, product, and samples digitally across your clinic to manufacturing operation using MES. Build in barcodes and labeling for scanning and checking throughout manufacturing. Using MES as part of a unified platform allows COC and COI to transition across the entire value chain, whether internally in manufacturing suites or externally across multiple sites and functions in the value chain.
7 Data Silos- Paper-based and disconnected point solutions separate and hide data and insight MES as part of manufacturing operations management application suite or unified platform digitizes business processes and collects records of all KPI data as a context rich data fabric across the whole operation. One source of truth, one architecture, curated data ready for reporting and business insights
8 Manufacturing Intelligence and business Insight Generate useful, accessible, contextual, curated data all in one place. Need data centric MES, not traditional process-centric. Break down data silos across applications and process stages.

ABOUT THE AUTHOR

Kevin McMahon, Precision Therapeutics Solutions Lead

Kevin McMahon is a pharmaceutical/biotechnology professional with 15+ years of industry experience in cGMP commercial manufacturing environments, specifically recombinant vaccine biotechnology and aseptic processes for fill finish. He has held progressing roles in leadership of operations and manufacturing science and technology groups in the industry before joining L7 Informatics as the Precision Therapeutics Solutions Lead. As the CGMP manufacturing SME, Kevin has influenced the strategy and requirements for building out L7|ESP as a unified platform that can tackle the manufacturing operational needs of our customers with a holistic and industry-focused approach. Kevin Holds a MSc in Business Analytics from UCD in Ireland and BEng in Electrical and electronic engineering from Queens University of Belfast, NI. This technical background, mixed with a career in process engineering, has given Kevin great insight into the challenges that face the industry. Kevin recognizes the need for solutions that break down data silos and paper-based processes to empower life science manufacturing operations management through connected technology.