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RockStep Solutions is revolutionizing preclinical drug discovery and helping get new drugs to market faster. RockStep’s cloud-based, end-to-end platform, Climb, enables discovery teams to aggregate and harmonize data, streamline laboratory workflows, search/collaborate across global sites and therapeutic areas, and ultimately get drugs to market faster.
Today, laboratories are forced to rely on spreadsheets, and outdated and/or cobbled together point-solutions to manage drug discovery research. However, as data volume and complexity increases, these systems struggle to scale, leading to major operational inefficiencies that are costing the industry billions of dollars annually: early missteps often go undetected, studies are needlessly replicated, valuable insights are often obscured, and time and resources are wasted.
And this comes at a time when clean, organized data, speed, and speed to market are so immensely valuable that unorganized, incomplete data is actually a major expense. Rockstep already has a growing customer base of more than 30 paying customers across the U.S. and Europe including:
The cost of developing a new drug has skyrocketed since the 1970s. A recent report published by the Tufts Center for the Study of Drug Development (CSDD) pegs the cost of developing a prescription drug that gains market approval at a staggering $2.6 billion over 10 plus years!
One day of operations costs up to $500,000, and one day of missed market opportunity can cost over $10M in lost revenue. Shaving days off the discovery pipeline is a strategic necessity for the survival of the pharmaceutical industry.
Specifically, data chaos in drug discovery costing is the industry billions annually:
Noncompliant. Data generated and stored uncurated and inaccessible in binders, spreadsheets, and point solutions
Slow to market. Patent clock ticking, slows time to market putting ROI and revenues at risk and market share in competitors pockets
Early missteps. Push the wrong drugs forward and leave cures undiscovered, billions lost annually
Wasted time and money. Unsustainable costs, inefficient for real-time and longitudinal analysis, human errors metastasize to billion dollar problems, data used only once, expensive studies replicated.
“Our data scientists probably spend 80% of their time right now on data wrangling... which is really a pain!”
- Bertrand Bodson Chief Digital Officer, Novartis
Drug development is a costly, high stakes, and highly competitive industry where operational efficiency directly impacts the eventual selection, cost, and frequency of new medicines made available to patients. Today, biopharma companies are struggling to stay competitive, hampered by pervasive operational inefficiencies and being overrun by endless streams of data, challenges that cost the industry billions of dollars annually and have a direct and negative impact on patient lives.
Spending on drug discovery:
August 2019: Novartis CEO in the hotseat after revelation to the FDA of falsified in vivo data. Novartis lost $5B in market valuation in one day. Climb’s in-vivo study module provides complete audit trails making data falsification impossible.
RockStep’s flagship platform, Climb, is the product of over $3M and 4 years of R&D conducted while working closely with the world’s leading experts in preclinical drug discovery research.
The Climb platform is uniquely positioned as a central data system for research teams and orgs, enabling each of the unique stakeholders within (e.g. scientists, lab and animal technicians, lab managers, veterinary staff, IT professionals, data scientists, etc.) to efficiently manage and collaborate across key laboratory processes, such as: experimental design, resource scheduling, animal breeding, biological sample tracking, laboratory workflows, and study protocol management.
It is the first and only end-to-end solution for the management of preclinical drug discovery on the market and the answer to the data chaos, process inefficiencies, and expense inherent to legacy systems and cobbled, point-solutions.]
Preclinical drug discovery is the crucial phase of research and development just before a new drug candidate moves into human clinical trials. It is hard to overstate how incredibly valuable cost, speed, and efficiency are at this stage:
Developing Cures. Each drug candidate represents a potential disease treatment for patients. These include patients suffering today, waiting for a cure, and those that have yet to become ill.
Odds Stacked Against. Only 1 in 10 drugs that enter into clinical trials is approved by the FDA for market. Taking into account this high failure rate and the associated expense when developing all in parallel, it is estimated that each successfully approved drug costs $2.5B+ to develop on average. And this has been trending in the wrong direction for some time - the cost to approval roughly doubled every ~9 years between 1950 and 2010 (1,2)
Incredibly High Stakes. It can cost a company up to $500,000 per day to run a drug discovery operation. But if they land a blockbuster drug, annual sales can reach $6.5-20B. (1)
Insanely Competitive. Drug companies are seeing their ROI drop rapidly as most of the easy drug targets have already been identified and are in late-phase clinical trials or are already covered by approved drugs. To remain competitive and profitable, organizations must become more efficient and improve quality with fewer resources.
A Race Against the Clock(s). In addition to the clock for each patient, companies must keep an eye on the IP clock as well. That’s because each novel drug compound is only firmly protected by its foundational patent for 20 total years following its discovery. Once the IP clock expires, competitors are able to copy the invention, placing the drug at risk to lose a majority of its commercial value overnight.
When talking about preclinical drug discovery, it’s safe to say that there are major incentives for companies to ensure that this phase of development runs swiftly, cost effectively, and efficiently. However, in practice, this is not what we see! In reality, the preclinical drug discovery space is suffering from a state of data chaos!
Mo’ Data, Mo’ Problems. At this phase of discovery hundreds of laboratory tests are conducted for each drug candidate as it moves down the development pipeline, generating enormous volumes of data along the way. And this challenge is only getting worse as the drug discovery process becomes increasingly complex. We’re tackling more complex diseases...taking advantage of novel insights gleaned from the computational analysis of massive data sets...leading to the generation of multi-target compounds, and multi-compound drug combinations...in turn, requiring more analysis and in-vivo testing...and generating more data...than ever before.
Outdated Tools and Organizational Silos. With a large number of individuals, multiple teams, and often various external service partners or collaborating organizations playing a unique and specialized role in this process, it’s a major challenge to keep the full data package linked together. As the data package gets passed along, updated, and passed along again, it inevitably gets segmented, stored across myriad spreadsheets, labeled in non-standardized ways, separated, inadvertently lost, or otherwise siloed off from other individuals/groups. And this is a pervasive issue - over 70% of preclinical R&D teams still rely on paper, spreadsheets, share folders, or homespun solutions.
Finding, Organizing, and Cleaning Data Takes Time. It’s not enough just to have the data. As efforts to develop new drugs and therapies rely more and more on large quantities of study data, the data corral is getting crowded. It is not unusual to find a single share folder with thousands of spreadsheets of study data. Highly skilled and expensive data wranglers are now needed to locate, quality control, merge, aggregate, and harmonize data for analysis.
Additionally, when analyzing large data sets, the results you get out are only going to be as good as the quality of data you put in. To get the most of the data collected, companies spend a significant amount of time on this step. In fact, data scientists currently spend ~80% of their time wrangling data as opposed to analyzing the data for insights and patient cures.
Bottlenecks and Redundant Work. Drug companies are struggling to aggregate and harmonize their data and manage their operations efficiently. In this fog of data, operational bottlenecks cause drug candidates to move more slowly through the development pipeline. And when data goes missing along the way, as is common, companies often end up duplicating the experiments and analyses to ensure they have what they need when it comes time for FDA review.
Ironically, More Data Can Also Improve Operations. You can only improve what you can measure. A majority of biotechs, pharmaceutical companies, and CROs struggle to collect actionable business intelligence about their preclinical operations. They are unable to collect detailed operations metrics to help make data driven process, hiring, and budget decisions.
As a result of these inefficiencies, ultimately, we all lose! Drug companies lose money and their competitive advantages in the market, and patients lose time and quality of life as they wait for new treatment options. It is imperative for all that drug companies find ways to improve the cost and efficiency of their operations.
Why Now? And Why Climb?
RockStep is arriving at a prescient time for the industry, leveraged by several powerful waves:
Industry Focus on ROI and Cost-Cutting. Drug development costs have doubled from $1B in 2013 to $2.6B in 2019, while ROI has dropped from 10% to 3% in that time. The only way for companies to survive is to figure out how to be more efficient.
Rise of Cloud, Digital and the Lab of the future. Legacy systems are expensive to deploy, secure, upgrade, and maintain. To modernize, laboratories are undergoing a digital transformation and becoming increasingly “intelligent” and virtual, continually optimized through the use of tracking sensors, real-time data outputs, learning and automation algorithms, and connected tools. Examples include:
Data storage, advanced computation, and analysis is all moving from on-premise to cloud-based computing. According to Gartner, over 75% of all biomedical research organizations have adopted a cloud-first policy when adopting new tools, and 50% of the top 25 pharma companies have started to plan for digital transformation.
Power of Clean Data. Per the CEO of Novartis: “the first thing we’ve learned is the importance of having outstanding data to actually base your machine learning on. In our own shop, we’ve been working on a few big projects, and we’ve had to spend most of the time just cleaning the data sets before you can even run the algorithm. That’s taken us years just to clean the datasets. I think people underestimate how little clean data there is out there, and how hard it is to clean and link the data”
Despite these mounting waves, disruption in the area of research operations and data management has been severely lacking. This lag is most apparent when you see that the industry’s status quo is the use of disparate spreadsheets and disconnected point solutions. The consequences of these approaches has long been leaving the industry with a laundry list of issues:
When taking into account this list, it’s easy to grasp why these legacy approaches are so poorly suited for the modern laboratory and why the industry is so excited about RockStep’s Climb and the thought of bringing their laboratories into the digital age.
Designed for Scientists by Scientists. The RockStep team is a dangerous combination of subject matter expertise and technical prowess - they are industry leaders with a deep experience in in-vivo research, drug discovery informatics, and the biopharmaceutical industry. They experienced the perils of data chaos first hand and decided to take it upon themselves to solve the known industry-wide issue.
With Climb, clients are able to more rapidly, efficiently, and cost-effectively work through early testing to understand a potential drug’s toxicity, dosing range, safety and efficacy profiles. Clients gain access to:
The company’s initial market target market of preclinical testing is estimated to be $21B (TAM). Climb is uniquely positioned in this market that includes tens of thousands of biotechs, CROs, and pharmaceutical companies. The company believes the portion of that market that is immediately serviceable by Climb today is $1B+.
The company sees a number of opportunities to build out specialized modules within the platform to increase the product’s reach, such as study visualization tools and customized features designed for CROs (contract research organizations) and non-clinical testing orgs that must abide by GLP (good laboratory practices). RockStep is also well positioned to move quickly into neighboring industries that are similarly being overrun by data chaos, such as Topical Ointments and Perfumes ($53B), Animal Medicines ($20B), as well as Agtech and Smart Farming ($10B).
Dive Deeper: read the RockStep Climb White Paper
Climb 1.0 was tested on site by world renowned organizations that went on to become paying clients. Today, the product is in heavy use by 400+ users across 30 client organizations in 14 states and Europe, every day, and rapidly expanding at a current rate of about 20 users/month. The rate of growth is projected to exceed 100 new users/month by the end of 2020.
Climb 2.0 is set to be released in February 2019. Climb 2.0 will take the transformation of in-vivo drug discovery in the cloud to the next level of operational efficiency.
The RSS team is comprised of seasoned industry veterans that have developed Climb using domain expertise gleaned from expansive careers and leadership roles at world renowned research institutions (Jackson Laboratory, Novartis, Biogen, Merck, Pfizer, Harvard Med, Charles River Laboratories, Boston Biomedical). Notably, the company also has experience taking similar companies from concept to scale to high valuation exits (~$100M).