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As a biotech company progresses from product concept to commercialization, it must implement the right IT systems at the right time. Here's a guide to when and where. 

By Paul King 

Sept 16, 2004 | When it comes to information technology requirements, the biotech industry is unlike any other. After all, how many industries must manage complicated processes like clinical trials, regulatory compliance, and contract manufacturing while hiring hundreds of expensive specialists over a 10-year product development span and spend $400 million with little or no revenue to show for it? While the stakes are enormous — in 2000, life science ventures captured more than $1 billion of investment seed capital — a successful company can provide significant return on early shareholders' investments.

To be successful, however, a biotech company must efficiently and effectively manage four main growth stages as it moves from startup to product commercialization. A key enabler of efficient and effective growth is the adoption of IT strategies specific to each stage. The four growth stages are:

  1. Startup
  2. Partnerships and trials
  3. Submission and commercialization
  4. Sales, manufacturing, and beyond

STAGE 1: Startup 
Stage 1 biotechs are often spun out of discoveries in an academic biology or chemistry lab. A typical startup may have five to 10 researchers and one or two business professionals with core competencies in science and finance. Usually the scientists have never worked outside of a university.

Stage-one biotechs are normally strong in science, fair in business knowledge, and dismal in the areas of regulatory compliance, clinical trials, product-quality assurance, and information technology. Yet by the time the biotech submits its first New Drug Application (NDA) to the FDA, it will have spent at least $3 million on IT alone.

Historically, financial managers assumed responsibility for technical decisions, but this approach has often failed to recognize or appreciate the complexities of the challenge. Today's executives at biotech startups must plan for rapidly evolving information systems, facilities, and supply chain, and develop an IT strategy that aligns with the overall business plan.

IT is no longer about merely providing computer-related services. It's about managing content, especially content tailored to regulatory requirements and submitted electronically to government agencies. Another content challenge is leveraging the knowledge from the ever-increasing data flow brought on by the genomic revolution. With high-throughput screening technologies and the emerging reliance on silicon techniques, the amount of data that scientists in a startup biotech must manage, store, and use will continue to grow exponentially.

Companies like IBM, Oracle, Sun, Motorola, and Agilent have created sophisticated tools that make the drug-discovery process more efficient. But managers must decide which systems — computers, databases, software, servers, and networks — are needed now and which systems can be added later.

On their own, scientists will tend to invest in isolated systems that have worked for them in the past without considering how the data from disparate systems will be integrated. Either through external consultants or hiring specialized staff, a startup will need to find people with systems experience as well as solid understanding of the scientific aspects of the business.

There are three main areas that a startup's IT infrastructure must harness: data, people, and cash.

With data, issues revolve around intellectual property and its protection. A stronger proof of concept is needed to gauge the value of the intellectual property and ensure its marketability. As the company grows toward the second stage and prepares for clinical trials, it will need to seek additional funding and potential partnerships. To secure both, it will bargain using the intellectual assets it has developed. These assets must be quantified and protected. With people, the significant issues are: How many are generating data, what are they doing with the data, and how many are on the payroll? With cash, the important concerns are how much is going out, how much is coming in, and finding new sources.

STAGE 2: Partnerships and Trials 
At this point the company is becoming externally focused through partnering, raising more money, and refining its business plan. The company is making decisions on how to develop a drug and take it to market. Does the company raise money itself, partner, or sell its technology? These strategic decisions will affect how much money needs to be raised, what equipment and systems have to be purchased, and what staff or services will be needed.

A significant milestone in stage-two growth is filing an Investigational New Drug (IND) application with the FDA. This is usually the first contact with the FDA and the time to define regulatory strategy. Success at this growth stage is contingent upon developing an electronic-submission strategy, or becoming "e-compliant." This will make the company more attractive for partnering or financing because it's expected that the FDA will soon make e-submissions mandatory. Building the necessary IT system and process controls early is easier and cheaper than waiting until later in the drug-development process.

Internally, the stage-two biotech is still science-focused as it hires more specialists. It's rapidly moving from ideas to proof-of-concept, and more money is being invested in labs and research work. Quality assurance (QA) is becoming more important as the company begins formally recording the process of how it does its day-to-day activities.

True, the FDA requires documentation of these procedures, but it's also simply good business practice. At this stage, electronic document management systems should become standard tools for handling document review, notice of expiry, and approval workflow, all of which lets staff concentrate on content.

Other new functions emerge in stage two, and critical strategic decisions have to be made. The biotech's systems must be capable of producing good information to help decision-making. To reduce risk and expense, many stage-two biotechs choose to outsource professional services such as pre-clinical and clinical research, legal counsel, and business development. However, outsourcing adds project management and cost-control functions to the growing list that now includes quality control, quality assurance, and regulatory compliance.

With research and finance dominating the biotech's priorities in the early stages of growth, the importance of information systems is often overlooked. As functions increase, management should solicit strategic advice from its IT department. For example, when selecting a contract research organization (CRO) to conduct clinical trials, the FDA now requires the biotech to show it has conducted a proper site/vendor audit to prove the CRO meets 21 CFR Part 11 regulatory requirements. IT and QA staff should conduct these audits together to measure the CRO's technical and procedural capabilities.

Collaborate or Die 
Each new external partner brings its own unique challenges, and IT must be consulted each time to avoid expensive mistakes. One biotech, for example, signed an agreement with a CRO only to discover six months later that the format of the data to be delivered was incompatible with the biotech's systems. All the deliverables that had been negotiated were focused on scientific and financial concerns, with no consideration of the data-delivery format. This led to unnecessary confusion and delays — a costly mistake.

With more partners and suppliers, the stage-two biotech needs to consider how its systems will interact with external systems, and the company must implement collaboration tools. If all researchers, whether internal or external, use collaboration tools and have convenient access to each other's clinical data, it's easier to pool knowledge regardless of location. Practical IT functions like document management help with collaboration, save money, and can be implemented simultaneously to meet regulatory compliance.

As the biotech grows to 100 employees, new departments are formed, each requiring its own tools to function. During rapid growth, companies sometimes develop systems without strategic consideration; each department struggles to get its needs met immediately, with little regard for system integration.

To save money, time, and resources the same tools with consistent formats need to be implemented across the enterprise. The senior IT person must be empowered to vet all requests and group them together for larger project consideration according to the priorities of the management team and the business strategy. Otherwise, problematic and decentralized systems develop far too easily.

One method of centralizing decisions is to form a committee to develop information systems strategy. A handful of members can represent a cross-section of the company and help set the direction and priority of current and future IT projects. This group should also discuss Part 11 risk assessment to scrutinize the impact of each new system's effect on regulatory requirements, and also to consider the impact on business operations.

STAGE 3: Submission and Commercialization 
The characteristics of a biotech in stage-three growth usually depend upon the decisions made in stages one and two. Partnering may have occurred, partner trials are typically being conducted in collaboration with a CRO, there are multiple business locations, and collaboration with universities is resulting in data that flow across different enterprises.

Generally, there's a lead product with multiple early-phase indications. There might be different trials at different phases, development of various drugs, and even the acquisition of new technologies designed to diversify the product pipeline. The stage-three biotech is constantly questioning what will make money and what will make for long-term business viability.

Now the defining state of the company is preparation for submitting a New Drug Application to the FDA. This mammoth publishing task involves the coordination of the entire company, its outsourcers, and its partners.

The submission process can easily be delayed, severely hampering time-to-market and costs. When labor costs, patent value, and opportunity costs are all factored in, the biotech at this stage has an estimated opportunity-cost burn rate of $1 million a day.

This is another reason why the biotech should already be fully outfitted for electronic submissions. E-submissions are a growing reality and the preferred format in the U.S., Europe, and soon Japan. Overall, any costs incurred in the implementation of document management systems are more than recuperated through time saved in the submission and review processes.

Reducing time-to-market by even 20 days can easily recover the IT expenses incurred up to this point.

Internally, the stage-three company is facing explosive growth of information systems (to handle time sheets, contracts, projects, laboratory monitoring, security, etc.), and for the first time there is rapid expansion of non-science staff.

Supply-chain management becomes more complex due to outsourcing, and production planning has to be exact as lead times for ordering are measured in months. The FDA requires consistency and control over the manufacturing process, and the uniformity of each product used in trials must be proven and documented. The biotech must also show it has a high degree of confidence that trials are being conducted appropriately. Quality assurance is crucial, as the FDA requires vendor audits as proof that all contractors adhere to protocols and agency guidelines.

Intellectual property management becomes more serious, too, as additional indications and patent protection extension are being examined. Marketing activity increases as the biotech looks at different applications for its drug and estimates the patient population while simultaneously scanning for potential competitors. On the operations side, quality control, staff training, facility management, and project management continue to consume more time.

The Trials of Clinical Research 
In stage three, the biotech may have between 100 and 200 employees. Human-resource information systems (HRIS) are now quite complex as stock options, salaries and benefits, and projects must be managed. With unique hiring needs, the biotech should task IT with developing a resume- and skills-tracking system to improve assignment of specialists and to take advantage of all staff capabilities. This helps dynamically reassign staff as projects are canceled and new research is started.

Reliable IT systems must also be implemented to manage the outsourcing of trials. Once a CRO finds patients that meet trial protocol, there's an enormous amount of information to record and track: patient and hospital name, patient's medical information, doctors' notes and files, data on patient reaction to product, and more. Plus there are legal contracts concerning experimental trials for each patient.

Each trial site and all the medical research conducted must be audited for submission purposes. This involves sending a monitor to the trial site to meet with the doctor and the technicians to review all of the supportive documentation relating to the trial. A uniform process is required to demonstrate to the FDA that procedures have been followed, and to document what was done if they weren't. It's critical that standard operating procedures (SOPs) are created, as the FDA will audit the trial sites themselves during its review.

With interconnected systems, the biotech can stop drug research in a more timely fashion, potentially saving millions of dollars. Collaboration tools enable real-time recording of data and provide up-to-the-minute information on clinical trials. These tools produce cleaner, more accurate data that's easier to publish during the drug-approval process. If everything goes right with the NDA submission, stage-three growth pretty much concludes with FDA approval of the drug.

STAGE 4: Sales, Manufacturing, and Beyond 
FDA approval of the biotech's leading drug is finally complete. Until now the company's primary focus was science, and everything was built around the NDA. Now what?

First, congratulations are in order. Only about 10 percent of initial research projects reach the submissions process, and only a small number of biotech firms are currently profitable. The new emerging function that occurs in stage-four growth is complex but a pleasure to deal with: revenue and cash-asset management. Money is now coming in, and an IT system is required to invoice, bill, and record deposits for thousands of clients. This new system must be integrated with existing systems.

Now marketing and sales functions need to be expanded to handle delivery of the newly generated demand. If it has partnered, the biotech may be able to tap into the sales resources of its largest partner to sell the product, but there's still the need to develop marketing strategy and track sales, whereabouts of customers, requirements of customers, and inventory.

This drastic change in the company's mandate has other significant effects on IT infrastructure. To handle the supply chain, production planning, trial management, project management, and all the other aspects that rely on information systems, IT will need to step up the real availability of data and build an enterprise resource planning (ERP)-style solution.

In the past, all data was targeted for one audience: the FDA. Now, in this stage, corporate data has a new audience: the management team. With a different audience come different needs. Rather than ask for verification of results, and proof of safety and efficacy, the management team will ask questions like How are sales in Europe? Is there money to hire more salespeople? Does the current rate of production match customers' needs and forecasts for growth in demand?

The Hard(ware) Side of Growth Management
The 4 Stages of Biotech Growth - And Their IT Needs

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A stage-four company's data requirements shift from actively tracking projects and trials to actively forecasting future sales — a difficult transition that needs to occur in less than six months.

Consider this: If a drug takes three months to manufacture, how does a company make sure it has enough supply to meet demand? Building a multimillion-dollar inventory before approval is a huge gamble, but enough of the drug has to be available for customers. This may significantly hit the bottom line.

If the company has added to its product pipeline or discovered multiple indications for its drug, the biotech could be in different stages with different drugs. Million-dollar questions requiring the most accurate information possible is being provided in real time the executive team. Now they must answer questions not asked as before as a research company. For example, after three months of sales of the approved drug, the biotech has a million dollars in revenue. Is it time for a shareholder dividend, or does that money go into research for the drugs in the product pipeline?

Superior IT, Superior Information 
Superior information and enhanced marketing forecasts lead to superior decisions. If the IT systems are built right the first time, efficiencies are gained and money is saved in the long run. In addition, collaboration, data sharing, and knowledge management tools will have captured a significant amount of intellectual assets, and it should now be possible to go back through the data to gain insight for new projects.

CCritical questions can be answered. How much did it cost to develop the drug? How were resources allocated? Where can improvements be made? Most important: How much more will it cost to develop another drug? The executive team now has a way to back up its gut decisions because projections can be quantified with existing data.

Business intelligence reporting emerges as a key function in the commercialization stage, and IT must give executives the tools and the training to run their own reports. Usually the easier a reporting tool is to use, the more complex the IT. Knowledge management tools are key, as data produced by each department (marketing, manufacturing, etc.) must be linked. This enables an executive to easily produce informative reports on the status of the entire enterprise.

Capturing intellectual assets through knowledge management tools can yield something else that's hugely valuable: additional scientific discovery. Data mining has enormous potential. With properly organized data from research, development, and clinical trials, the biotech can use data-mining techniques to go back and "discover" new indications.

One more thing a well-evolved IT structure can provide: Many biotechs have found that by building intranets that link databases, their scientists can become aware of projects other scientists have already tried, thereby reducing duplicate work and learning from past successes.

Paul King is director, life sciences, for Pacific Coast Information Systems, an IT services provider. E-mail: 


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