In computer search optimization theory, active information is a measurement of a search algorithm’s internal information as it relates to its problem space. While it has been previously applied to evolutionary search algorithms on computers, it has not been applied yet to biological systems. Active information can be very useful in differentiating between mutational adaptations which are based on internally-coded information and those which are the results of happenstance. However, biological systems present many practical problems regarding measuring active information which are not present in digital systems. This paper describes active information, how it can be used in biology, and how some of these problems can be overcome in specific cases.