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Information technologies can improve clinical trial quality and efficiency
Expert offers look at some systems that work well
The need for less expensive and more efficient clinical trials has increased in recent years with drug discovery occurring at an explosive rate, and yet the clinical trials process has changed very little over the past decade, an information technologies expert says.
"You have a huge bottleneck with clinical trials, and this is a cost driver that is increasing the social cost of health care and threatening, at some point, to make new compounds unattainable," says Russell J. Clark, JD, president of Cancer Technology Applications of Atlanta. The company consults with institutions to put together the right suite of applications to facilitate clinical trials from the recruitment stage to data capture.
"Cancer is an example of where certain new treatment regiments cost $100,000 per patient per year," he says. "Where you can save money is in the clinical trials process, which is primed for dollar savings."
For example, the clinical trials process could use re-engineering and technology applications to reduce the overall time and cost of clinical trials, Clark notes.
"Seventy percent of the total cost of drug development is spent during the clinical trial process," he reports. "The average cancer drug takes 10 years to get through the drug development process."
A recent study found that the average cost to develop a new drug is $900 million for a pharmaceutical company, but another study estimated the cost to be closer to $1.7 billion, Clark contends.
"So it’s a lot of money; and my point is that a huge percentage of that cost is wrapped up in clinical trials," he says. "I’ve spent a significant amount of time in the last five years helping to re-engineer and develop better processes."
From his research into new technologies, Clark offers this brief guide to what will work in making the clinical trial process more efficient and cost-effective while maintaining or improving quality:
One of the challenges is to match the potential clinical trials subject and physician, especially for cancer trials, he notes.
"You will never get the patient on the trial without the physician being there to educate the patient about what the trial is about," Clark says. "A person can go on a web site to find a trial, but unless it matches back to the treating physician, there isn’t much value to finding someone that way."
So he has worked on identifying systems and technologies that will match potential subjects with physicians.
"You need a sophisticated data mining operation that searches structured and unstructured data," Clark explains. "To match the characteristics of a patient with a trial, you need to dig deeper than demographics."
For example, it’s possible to match patients using structured data, such as demographics, ICD-9 codes, physician identifiers, and PCT codes, but this method would produce a lot of false positives, and most physicians would not be interested in this method, he says.
"Physicians want more accuracy, and an unstructured data mining tool would allow you to go into the physician’s notes and do a much finer search," Clark says.
Here’s how challenging the unstructured data mining can be without the help of technology: "In Florida, one customer [gave] me an example of where she’d gotten a request from a pharmaceutical company to find 50 patients for a cardiovascular study, and she and three of her employees went through 30,000 paper charts," he recalls. "Out of that, they found 40 patients."
The other old-fashioned way patient recruitment works is for clinical trials administrators to invite physicians to lunch and then ask them if they have any patients or to give out business cards to physicians who have a high volume of patients who potentially will meet the study’s criteria, Clark says.
"So we haven’t applied technology effectively in terms of patient recruitment," he says. "And I believe there are tools out there that will do that effectively."
One such tool is PolyAnalysis, sold by Evrika in Aliso Viejo, CA, Clark reports.
"PolyAnalysis will allow a user to go into a research site that has patient data in electronic format, including patient information, ICD-9 codes, structured data, lab results, and transcribed unstructured notes," Clark says. "Most hospitals have these components in electronic format, and you would need to import the data from the system and import data from any electronic program and do a search by eligibility requirements."
The output is a report that identifies each patient who meets eligibility requirements and the patient’s identification number, he adds.
Then, all a clinical trials administrator would need to do is contact the physician and let him or her know that there’s a clinical trial for which this patient’s identification number appears to fit the trial, Clark says.
"You could attempt recruitment and enrollment through that means," he says.
There are many web sites that offer to do this type of search, but most do not appear to do an adequate job of matching the provider and patient, Clark notes.
And while the American Cancer Society is working on a web site matching program, it’s not yet public, he says.
Most clinical trials continue to use paper forms, he notes. "So the patient visit data are captured relative to the visit recorded in the source document," Clark says. These data include patient history, lab testing, physical exam, and patient charts.
The clinical trials administrator then takes the source document and patient chart and transcribes these into a case report form using the relevant information.
"This is highly inefficient and error-prone, but that’s the way we do it," Clark explains. "There have been 60 little companies sprung up in the last 10 years to address this issue; a number of them have failed and gone out of business."
Pharmaceutical companies have continued to be extremely conservative in terms of changing this practice, he adds.
"A few have developed systems, but many of the others march down the paper trail," Clark says.
"I think we’ll see some dramatic changes in the near term," he predicts. "There’s a stability, proven track record, and proven technology capabilities with the big players who’ve entered the field, so I think we’ll see a major paradigm change there."
Besides being slower, the paper process has more chances for someone to make a mistake with data.
"What happens with paper is the facts are mailed to a central data site and double-entered into an electronic database," Clark explains. "There are two people entering the data under the theory that they won’t both make the same mistake; so data is reviewed to see if there’s a difference between data entry person one and two, and if there’s a discrepancy, it needs to be resolved."
To resolve a difference, the clinical trials administrator is called to clarify the discrepancy before the data officially are entered into the database, he points out.
"That can take weeks from the time of the visit to when the data is entered and queries resolved, and it finally goes into the research database," Clark says. "Juxtapose that with an electronic system in which the data goes in and has its own logic so it won’t let you enter, for instance, a 2-foot-tall man into the data site, and it can’t make that kind of mistake."
This sends data to the research base quickly, and if there are any discrepancies when it’s monitored, these are electronically taken back to the site and resolved, he notes.
"Adverse events can be tracked immediately; and if a trial is going in a bad direction, they can stop it," Clark reports. "Most of the money is spent by trials that go on and on and should be stopped because they’re not showing efficacy."
With an electronic data process, a clinical trials administrator will be able to look at the data more quickly and make smarter and faster decisions, saving money, he adds.
Then taking electronic data collection to the next level, there is an electronic medical record that flows and populates the field in the case report form with no double entry, Clark says.
"There’s a lot of work on that right now, with a lot of industry leaders and private-public consortiums that have adopted standards so various clinical trial data systems will talk to each other," he says. "There’s a push from a number of major players to develop interfaces and integration between clinics and electronic data capture systems."
For example, Microsoft Corp. of Redmond, WA, is entering the field, and Siemens Medical Systems Inc. of Issaquah, WA, is in the business and is the most advanced in terms of integration with other systems in terms of electronic data capture, Clark reports.
It’s more efficient to make PDF files of regulatory documents and e-mail these to IRB members, rather than to mail thick packages of paper, Clark notes.
Most multicenter studies have a separate IRB reviewing the same protocol conducted at the different institutions, and this might mean that a clinical trial will take many months to complete the IRB approval process, he says.
"A better process we’ve been working on with a number of sponsors is a centralized IRB, where there may be 10 sites and one IRB," Clark says. "This is one of those dinosaurs that dies hard."
Protocol training could be improved through the use of a web-based education format, he says.
It would save travel costs, investigator, and clinical trials staff time because they could learn about the protocol at a time that is convenient for them rather than attending one big meeting, Clark adds.
And the web-based program could test participants to make certain they understand the protocol, so this would meet all regulatory requirements, he says.