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At the Vanguard of the Life Sciences Digital Transformation Wave


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Summary: Learn how to leverage digital transformation strategies and cloud lab platforms for faster drug discovery using closed-loop, design, make, test & analyze automation systems.


Introduction

In the late 1800s, the world wanted a faster horse, so Henry Ford built the world a horseless carriage - the car. In our era, drug discovery needs more rapid discoveries and innovation. However, using our existing methodology and infrastructure creates bottlenecks and inefficiencies that curtail and delay the discovery of new life-saving therapies.


Like Henry Ford did for the transportation industry, Strateos has affected a paradigm shift for the life sciences industry. They are initiating a convergence of information technology and science, thereby becoming the leading edge in the life sciences and digital transformation wave. They have created the world’s first Cloud Lab Automation-as-a-Service (CLAaS)

platform to reimagine the lab as a rich data center to progress the life sciences at a breathtaking pace. And they help their clients turn their digital transformation into a business transformation.


Before we share the benefits of partnering with a digital transformation enablement organization like Strateos let’s take a step back in time and look at the origins of drug discovery to grasp the strides we have made thus far.


Let’s begin our journey when technology was not part of the equation; drug discovery goes back thousands of years. Before modern innovations, drug discovery was based on more primitive observations and experimentation with natural products like plants, flowers, and fungi. Some examples include:



In the 1600’s, Swiss alchemist Paracelsus von Hohenheim created laudanum, known as tincture of Opium today, and contained almost all of the opium alkaloids, including morphine and codeine as well as gold and pearls. This pain killer and cough suppressant was probably one of the earliest examples of a “medicine” and germinated the seeds of the pharmaceutical industry.


The next colossal leap took place in the 1700’s, when the earliest inoculums were prepared for smallpox. William Withering used his interest in botany to discover a treatment for dropsy by extracting digitalis from the leaves of the foxglove. James Lind revolutionized the British Royal Navy when he discovered that scurvy was related to a lack of Vitamin C, by performing arguably the first controlled medical trial.


The 1800's brought us further discoveries and medicines such as:



As scientific innovation progressed in the 1900s, drug discovery became more systematic and took an industrialized approach. The process evolved to screening natural products and then isolating the active ingredients.


Synthetic versions of natural product(s) were produced where the chemistry wasn’t too complicated. The disadvantage at that time involved safely testing these ingredients. In fact, many early chemists would test compounds on themselves and then record the outcomes-if they survived! Fortunately safety and toxicity studies have significantly improved since these early days.


With the advent of the mainframe and personal computer, drug discovery has become one of the world’s most complicated and technical businesses. At this juncture of scientific progress, advanced lab automation, digitalization of the laboratory, and the power of an in silico-first approach are all rolled up under the latest Cloud Lab infrastructure. An automated loop of Ideate, Design, Simulate, Make, Test, and Analyze will put human intuition, creativity, and ideation to the test and has the potential to catapult results beyond our expectations.


This concept can drive down cycle times, make science reproducible, and drive FAIR data and process principles. All of which will only enhance the future in silico-first efforts with more model quality data. We are entering a new phase of computational chemistry where scientists are edging ever closer to designing and predicting active molecules.


Though it has taken over 375 years to reach this point of advancement, the exponential speed of innovation could take us even further in the next 375 years. We are now driving much faster cycle times with ideas being quickly validated with automated, diverse, and novel synthesis followed by rapidly generated screening data. Like Cloud computing, your Cloud experimentation and testing are remote, secure, and highly efficient.



Because of the cutting-edge nature of these R&D technologies, many scientists are unacquainted with the benefits they provide. These include high throughput experimentation (HTE), advanced lab automation, and in silico-first or model-first approaches to R&D.


However, precisely because these methods are so new and rapidly-evolving, users can experience some change management issues and consequently encounter failures. As is often true, innovation has outpaced mainstream acceptance. For example, in 1963 DARPA (the Defense Advanced Research Projects Agency) partnered with MIT for what has now become collectively known as cloud computing.


The availability of cloud computing to the public started with Amazon Web Services in 2006, and IBM and Google followed suit a year later in collaboration with several universities. The goal of this collaboration was to provide cloud computing to all universities.


See https://en.wikipedia.org/wiki/IBM/Google_Cloud_Computing_University_Initiative


Microsoft got into the game several years later, in 2010. The point is that it took another 10-12 years to become “mainstream” in the R&D industry, with some compromise.


Although the internet took about ~30 years to go mainstream, revolutionizing the world as we know it, it took cloud computing ~40 years to reach that kind of acceptance in the R&D industry.


Despite the predictable nature of how innovation is accepted by the mainstream, the quality of efficiency gains and reliability of data for companies and ultimately for humanity are too valuable to be postponed. Cloud Labs need to become mainstream much sooner!



Industry Adoption Can Be a Very Slow and Painful Process

So what are the challenges to widespread adoption of Cloud Labs by R&D organizations in the 2020s? While not surprising, these challenges mirror the experience we have had with cloud computing!


The top 10 reasons are:


Strateos: Cloud Lab Innovators

Founded in 2012, Strateos has gathered R&D-experienced experts along with life sciences, data scientists, software and automation engineers. They have built a first-generation Cloud Lab that is dramatically changing the way a majority of drug discovery experimentation and testing are performed.


Not only can clients run samples in these remote control, remote access smart labs, but Strateos also partners with their clients to build and run their private cloud labs, ranging from single automation workcells to global facilities.


By integrating both scientific hardware and virtual infrastructure and software, scientists are liberated from managing the complexities of disparate hardware and software systems, enabling greater focus on designing experiments, developing new hypotheses and generating reproducible data in an automated fashion.


Strateos is leading these innovations for their clients. They work with their clients by providing technology and digital transformation-enabling services, thus accomplishing efficiency gains at lower costs.


They accommodate the needs and concerns of their Fortune 500 clients and emerging life sciences organizations. One of the most challenging obstacles they face is in change management and adoption. Fortunately Strateos has the tools and knowledge to help their clients overcome these obstacles.


Strateos helps their clients define and turn their digital transformation into a business transformation through unique services and product lines:


  1. Control Our Lab - Remote control and automated cloud labs that are accessible from a web browser enabling scientists around the world to easily access and control new technologies, drug discovery, cell and gene therapy and synthetic biology workflows.

  2. Control Your Lab - Cloud lab automation software enables organizations to control their own scientific instruments and laboratories locally and worldwide, schedule workflows and manage their scientific data.

  3. Build Your Lab - Strateos’ smart lab facility design-build services helps organizations build their own smart labs and facilities.



Strateos has brought together an incredible team of experts, capabilities, compliance, security, and know-how which translates to the “Art of the Possible’’ in their Idea-to-Data Project; the automation of the DMTA cycle.


Their creation is the real “Lab of the Future”, but you can access it now! On par with the same kind of paradigm shift cloud computing has already created in your R&D organization, the efficiency gains created stand to greatly benefit you. So whether you are a startup, academic, in silico discovery, or a mature R&D organization, a Cloud Lab should be on your prioritized list of organizations to partner with.


The Idea-to-Data benchmark study demonstrates improved efficiencies of an automated Design-Make-Test-Analyze (DMTA) cycle. Strateos virtually and physically integrated chemical and biological experimental components of the drug discovery process to enable researchers to select structures that can be prepared on automated systems and made available for follow-up biological testing, allowing for timely hypothesis testing and validation.


The goal was to illustrate the current processes for ‘closed loop’ drug discovery or lead optimization by synthesizing 14 structural analogs of the selected model compound, tofacitinib, purifying the analogs, and testing them in kinase inhibition assays (JAK1/2/3, TYK2).









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