Go Digital, But Make It Effortless: Pharma Recipe Authoring

  • Published:
    Aug 23, 2022
  • Category:
    White Paper
  • Topic:
    Digital Transformation

Executive Summary

More than half of US adults rely on pharma medications to manage conditions and extend their lives. As such, recipe authoring is one of the most critical phases of drug development.

Done on paper, recipe authoring can lead to transcription errors, process delays, and costly deviations. When done using a legacy or traditional MES, it takes months or years to configure, requires numerous experts and coders, and results in a mountainous heap to manage for years. But when done efficiently, leveraging modern techniques and tools, time-to-market is reduced — meaning people receive the medications they need sooner.

In this white paper, we’ll explore some of the most commonly encountered challenges associated with recipe development and how going digital enables companies to turn molecules into medicine in a fraction of the time.

Jump to…

Recipe Development: An Overview 

What is a pharmaceutical recipe?

In order for manufacturers to produce high-quality, trusted medications in compliance with the FDA, they must document the process. This “document” is referred to as a recipe, and ensures that the correct process is followed and controlled in each and every dose. 

How are pharmaceutical recipes developed?

Recipe development is a complex process that begins with molecule discovery and ends with perfected, commercial-ready instructions. The overall goal is to determine how to scale drug development without sacrificing quality, safety, or efficacy.

It’s both a science and an art — requiring immense attention to detail so that recipes can be replicated to a tee across sites. As such, it comes as no surprise there are various stages researchers must work through to optimize pharmaceutical recipes. These include:

  • Preclinical: During preclinical development, researchers work to figure out the best way to create the drug recipe (based on a specific molecule).
  • Clinical: When the drug moves on to clinical manufacturing, the question becomes, “How do we scale and optimize this recipe?” This involves refining the recipe as researchers assess how to make a consistently high-quality product.
  • Commercial: As the product is transitioned to commercial manufacturing, the recipe needs to be scaled and “hardened,” or made suitable for mass production. At this stage, the job of the recipe is to ensure instructions are followed perfectly and the process is recorded and controlled to support compliance and consistency.

Can pharmaceutical recipes be authored manually?

Authoring a recipe that is repeatable, reusable, readable, and executable can take months to years.

This is due to a number of factors, including:

  • Multiple handoffs across stages and teams
  • Numerous tools that house recipe information
  • Differing scales and compliance needs across stages
  • Variations of the same process across different sites

Naturally, the recipe will evolve throughout the drug development lifecycle. As such, it’s imperative to document every process in its entirety. This will ensure the paperwork is accurate when it comes time for regulatory approval or audits.

What is a batch record?

A batch record is a document (paper or digital record) that captures every point of activity and detail that went into making the batch of drug. It details the ingredients, quantity, equipment, and steps taken — as well as the dates of completion — to create a specific batch of product. 

How do you write a batch record?

Writing a batch record involves defining what should be documented throughout the process of producing a batch of drugs for compliance, quality and review purposes. There are many different parties involved in defining what is truly required to be documented. Information flows from the chemists to the engineers, and eventually the process technicians and quality managers.

Here’s a snapshot of who’s involved and to what extent: 

  • Chemist: Defines the steps taken to create the molecule and which parameters must be controlled and documented to produce the molecule 
  • Engineer: Outlines the automation or equipment process needs, as well as the instruments and settings are required to be documented and reproduce the results
  • Scientist: Takes the data from the chemists and engineers, and defines what steps and critical process parameters need to be documented and monitored
  • Quality Managers: Defines what critical quality attributes need to be recorded and monitored and what scenarios or bounds should be flagged as exceptions
This cross-departmental collaboration results in a batch record, which is then used as a guide for drug manufacturing.

Recipes vs batch records

You might be asking, “How does a recipe relate to a batch record, and what’s the difference?”

These terms tend to be used interchangeably in the industry and are the source of confusion and sometimes conflict. While the jury is still out on the official name and difference, at Apprentice we try to alleviate the confusion with the following distinction:

  • Recipe: The documented process, instructions, way a drug should be produced
  • Batch record: The executed, or filled out, version of a recipe for a given batch of drug

Essentially, a recipe should serve as the starting point of a batch record. You should be able to follow and fill out a recipe and end up with a batch record of what you did. Now, many organizations have preferences of adding extra information into a batch record that makes it more of a report, but the executed recipe is always the main source of information.

Why Is Recipe Authoring so Crucial in Pharma?

Picture this: you’re dining at your favorite restaurant, browsing the dessert menu. You decide to order a gluten-free chocolate cake with chocolate icing. But what they bring you is a vanilla cake with chocolate icing, both containing gluten.

You’d probably send the cake back and complain, right? Not only is it not what you wanted, it’s potentially dangerous for those with a gluten intolerance to consume.

 This scenario is a “vanilla” version (pun intended) of what happens when pharma recipe authoring goes wrong. Without proper records, including step-by-step instructions, it’s impossible for manufacturers to make exact replications of drugs.

That’s why documenting each process followed with pictures, logbooks, and reports is so crucial. It ensures there is a paper trail readily available to reference, in the event something goes wrong. It also clearly defines and documents the boundaries and values that should remain in throughout the process, so that it can clearly be identified if something is out of range and a deviation needs to be logged.

“Starting in preclinical, use documentation to collaborate early on potential recipe puzzle pieces that can be parameterized and templatized so that reusability becomes a norm.”

— Emilee Cook, Product Lead, MES, Apprentice

Plus, documentation accounts for all possible variables and guarantees the drugs manufactured are the same — even if they’re manufactured by different companies or in different locations. This way, when it's time to initiate a tech transfer between sites, teams, and stages of drug development, the information is accurate, organized, and easy to understand.

What are the Top Challenges to Manually Authoring Drug Recipes?

Recipe authoring is no joke. It’s a time-consuming and resource-intensive process that aims to standardize recipe development, from research to production, while maintaining the integrity of the product. 

It also comes with its fair share of challenges. These include:

  1. Transcription errors. Typos and misspellings happen, especially when researchers record recipes by hand or via an electronic notebook. These errors lead to delays in recipe development because they have to be identified and fixed before drug development can continue. 
  2. Data overload. Process scientists typically author various recipes at once. As such, papers sit on their desk for days, or even weeks, waiting to be reviewed. Keep tracking of all multiple datasets at once takes time and effort.
  3. Lengthy review cycles. In many larger facilities, technicians run from one building to another to get signature approvals, creating bottlenecks in the flow. Plus, review cycles are lengthy as the data has to be checked and cross-checked by different stakeholders. 
  4. Data management issues. Once the authoring process is complete, the raw data, often in paper form, is archived and maintained. Unfortunately, organizing and managing paper files isn’t easy — especially when drug development is ongoing. 
  5. Knowledge transfer cycles. Transitioning a recipe from one person or one team to another across the drug lifecycle many times means piecing together hundreds of documents from different tools and systems and trying to make sense of it all across multiple teams and sites.

Fortunately, equipped with the right solution, scientists can accurately and efficiently author new recipes and evolve recipes across the drug lifecycle — sans the challenges listed above.

What Modern Solutions Address These Challenges?

Nowadays, recipe authoring doesn’t need to be a manual process. Instead, scientists can leverage technology like Microsoft Word, electronic notepads, and cloud-based manufacturing solutions to expedite data capture. 

These solutions are: 

  • Easier to maintain records and archive
  • Shareable via links versus in-person
  • Editable by multiple stakeholders at the same time 

Here’s a synopsis of the modern solutions available, along with the pros and cons of each:

  1. Microsoft Word. First launched in the 80s, Microsoft Word (and similar paper-on-glass tech) is a step in the right direction, and mitigates some of the challenges associated with keeping records in physical form.

    However, Word also has a serious Achilles' heel. For starters, it doesn’t integrate with anything — meaning all of the information recorded and documented across teams is disparate. Secondly, it doesn’t allow for a complex process flow, so it’s difficult to accurately account for potential variables. Thirdly, you still have to print these documents out for operators to fill out during execution, which means there is no real-time guidance or checks.
  2. Digital platforms. These platforms make it easier to author and execute digital recipes. They’re usually customizable, and created specifically for the life sciences. However, they’re usually not cloud based, which means they’re harder to implement and typically only available on-premise. This approach to recipe authoring also requires highly trained SMEs or skilled programmers, who are quite costly to employ. That’s why this deployment approach brings a higher cost and longer time to value. It can take years to see a return on investment, versus cloud-based solutions that can pay for themselves within months or even weeks.

    In addition, on-prem architecture requires extensive IT management, limits the ability to receive new product features, and cannot provide the same scalability as the cloud. It also prevents true, live collaboration across many teams and sites.
  3. Cloud software. Unlike on-premise servers, cloud platforms do not need dedicated privately owned hardware, or data centers, to function.

    Instead, cloud software is offered à la carte, allowing companies to only pay for what they use and adjust resourcing as they scale their business. This allows businesses to lower overhead costs by eliminating the need for dedicated IT infrastructure, IT workers, and server maintenance.

From a recipe authoring perspective, cloud software enables true enterprise recipe sharing, cross-team collaboration on authoring recipes, and higher execution performance.

But just building or using cloud-native software for recipes isn’t unlocking its full potential.

If the legacy digital systems just put their same functionality in the cloud or even made it cloud-native, that still wouldn’t make authoring a recipe easy.

“Automate with purpose — not just because. Get value out of your digitalization efforts by re-envisioning a better process, not just a digital one.”

— Emilee Cook, Product Lead, MES, Apprentice

As an industry, we must elevate the recipe experience in order to get drugs to patients faster. In their Digital Plant Maturity Model, BioPhorum shows the way with a series of levels organizations can reach:

While paper-on-glass solutions are a step in the right direction, software should be intelligent and fully integrated to truly unlock the power of Pharma 4.0

But we can go even further. Why stop at Level 3 where most legacy systems are today? 

In order to make recipe authoring easy, we need to:

  • Make it seamless to define a single recipe for your organization that is shared across many teams with just a few clicks
  • Provide easy transition mechanisms to evolve and move a recipe from preclinical to clinical to commercial, streamlining the tech transfer process
  • Reimagine authoring tools for the actual scientist instead of a programmer or MES expert, by aligning the recipe to the science and process
  • Embed smart features directly into the authoring tool so that things like integrations, state changes, exceptions, and complex navigation rules are configured in a matter of minutes instead of hours/days
  • Optimize the user experience for recipe authors, operators, and supervisors by factoring in all the different workflows each end user will take

At Apprentice, we’re proud to say that this has now become a reality

Our Take: Recipe Authoring Should Feel Effortless

And with the right tech, it will.

Do yourself and your team a favor, and start leveraging cloud-based technology. The cloud allows you to free up your IT team, quickly scale up or down drug development, and seamlessly capture, share, transfer, and access relevant data.

The cloud makes recipe authoring digital, but effortless. Our only question is, why sink when you can fly?

Our Featured Thought Leader

When it comes to the future of pharmaceutical recipe authoring, Emilee Cook is our in-house expert! Meet Emilee and learn about her unique approach to MES in the pharmaceutical space:

Emilee’s background

Emilee leads software development teams at Apprentice, tapping into user data to build better products and improve experiences for manufacturing personnel. Emilee actively works with pharmaceutical manufacturers, designing software to accelerate technology transfer, support modular manufacturing, and increase product quality throughout the drug lifecycle. 

Over her 10 years in the life sciences, Emilee has spent time in R&D producing biomimetic devices at Draper Laboratory, developed Syncade solutions for 260+ customer issues, founded new user-driven product development approaches, and crafted strategies for next-gen pharma solutions at Emerson and now at Apprentice.io. Promoting women in STEM fields is one of her passions and you’ll find her speaking at local universities and teach-in events in her community. She recently won Manufacturing Institute’s STEP AHEAD Emerging Leader Award for 2021 for these efforts. While she is an engineer at heart, Emilee is also a creative. She’s certified in human-centered design and facilitation, and you’ll often find her painting and crafting in her free time.


Emilee’s recipe authoring recommendations

Apply an agile approach to digitalization of batch records to achieve value sooner.

  • Define recipes iteratively for process development and evolution. Start small and simple and grow. What if you added in equipment integrations later and just started simple at first?
  • Define a true MVP and clear priorities. Just because it is possible doesn't mean you have to prioritize doing it right this second.
  • Consider simpler process recipes. I once watched a team implementing an MES go from paper to Visio diagrams that when printed out covered an entire wall and a half of a conference room. But was their paper batch record flow and process that complicated? I highly doubt it.


  1. BioPhorum. (2022, April 4). Digital plant maturity model (DPMM) version 2: A best practice guide to using the DPMM and assessment tool. biophorum.com
  2. Cao, H. (2018, May 10). A Systematic Framework for Data Management and Integration in a Continuous Pharmaceutical Manufacturing Processing Line. MDPI. mdpi.com
  3. McLaren, M. (2021, December 6). The future of paper batch records in pharma’s digital transformation: a case study. Pharmaceutical Technology. pharmaceutical-technology.com
  4. On-Premises vs. Cloud: Pros and Cons of Each. (2021, December 8). Teradata. teradata.com
  5. Prescription Drugs. (2019, February 13). Health Policy Institute. hpi.georgetown.edu
  6. Recipe Development Process Re-Design with ANSI/ISA-88. (2014, June 3). Intech. Retrieved June 24, 2022, from journals.sagepub.com