On Friday, the U.S. Food and Drug Administration issued guidance on Bayesian statistical methods in the design and analysis of medical device clinical trials that could result in less costly and more efficient patient studies.

Bayesian probability is one of the most popular interpretations of the concept of probability. The Bayesian interpretation of probability can be seen as an extension of logic that enables reasoning with uncertain statements. To evaluate the probability of a hypothesis, the Bayesian probabilist specifies some prior probability, which is then updated in the light of new relevant data. The Bayesian interpretation provides a standard set of procedures and formula to perform this calculation.

This entry was found in Wikipedia:

Bayesian probability interprets the concept of probability as "a measure of a state of knowledge", in contrast to interpreting it as a frequency or a physical property of a system. Its name is derived from the 18th century statistician Thomas Bayes, who pioneered some of the concepts. Broadly speaking, there are two views on Bayesian probability that interpret the state of knowledge concept in different ways. According to the objectivist view, the rules of Bayesian statistics can be justified by requirements of rationality and consistency and interpreted as an extension of logic. According to the subjectivist view, the state of knowledge measures a "personal belief". Many modern machine learning methods are based on objectivist Bayesian principles. One of the crucial features of the Bayesian view is that a probability is assigned to a hypothesis, whereas under the frequentist view, a hypothesis is typically rejected or not rejected without directly assigning a probability.

One of the most difficult challenges in the cannabis revolution movement is of course "personal belief" systems.  The Examiner.com comment board below is an excellent place for readers of this column to expand upon the many ways in which legislators, the DEA, the FDA and others have based the War on Drugs and current cannabis legislation on their own personal belief systems.

The news of this new Bayesian guideline is one that the medical marijuana community should be able to effectively use in arguing against bad legislation. For example Colorado's SB109 which would restrict patients' access to their medicine despite the fact that the citizens of Colorado voted in favor of it. Legislators write SB109 and other laws,  vote no on pro-medical marijuana legislation based upon their own personal belief systems.  They would now be unable to their personal beliefs as much weight.

Since the Agency says Bayesian statistical methods could trim costs, boost efficiency, marijuana advocates would be able to prove that prohibitionist legislators are wasting tax payers money.

Even more exciting is the concept that through the FDA's own ruling the movement could use this argument against the FDA itself to as a tool in removing the prohibition.

Please click here to read the text of the FDA press release.

Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials

The following note is attached to the above page:

Contains Nonbinding Recommendations

Preface

Public Comment

Written comments and suggestions may be submitted at any time for Agency consideration to the Division of Dockets Management, Food and Drug Administration, 5630 Fishers Lane, Room 1061, (HFA-305), Rockville, MD, 20852.

Alternatively, electronic comments may be submitted to http://www.regulations.gov. When submitting comments, please refer to Docket No.2006D-0191. Comments may not be acted upon by the Agency until the document is next revised or updated.

Hopefully the best lawyers in our community will stay on top of this new guideline.  Spread the word.

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