PROAST has been developed at RIVM for the analysis of toxicological dose-response data. It can be used for dose-response modeling of continuous, quantal or ordinal response data, and for deriving a Benchmark dose (BMCL) in human risk assessment, or an ECx in ecotoxicological risk assessment.
Currently, PROAST is based on multiple choice questions that guide the user through the program. Next year a version will be released that is based on a graphical user interface (GUI), which should make the use of PROAST even simpler. PROAST is suitable for an in depth analysis of a single dataset, but also for a quick (automated) analysis of a whole series of endpoints (responses), which may be useful for analyzing complete studies. Apart from applications in human or ecotoxicological risk assessment Proast can be used for nonlinear regression in any other field of science. 

Some further specifics are:

• Different subpopulations (e.g. males and females, rats and mice, subchronic and chronic exposures) can be analyzed as a combined dataset. Thus, it can be tested if the subpopulations differ significantly in sensitivity (strength of response). This approach at the same time results in an efficient use of the available data.
• Nested data (e.g. litter effects in developmental studies; housing effects when animals are grouped in different housings) can be dealt with. 
• PROAST includes two families of five nested models (exponential and Hill, respectively) from which the optimal model for that family can be determined automatically. 
• The analysis of the dose-response data can be directly followed-up by applying probabilistic Assessment Factors (AF), to arrive at a Probabilistic RfD. In addition, by applying probabilistic AFs one may derive a distribution for the predicted effect size in the sensitive human population.
  

PROAST vs. BMDS

USEPA developed the BMDS software, which is also suitable for dose-response analysis and deriving a BMDL from dose-response data. Currently, efforts are undertaken to achieve consistency between the BMDS and PROAST software.

Compared to the BMDS software, PROAST has some advantages and disadvantages. Advantages are that PROAST has more options and flexibility compared to BMDS, such as including covariates in the analysis, and changing the plotting options. The main disadvantage compared to BMDS is that it is less easy to get PROAST working for the first time. Some initial effort (up to one hour, depending on personal skills) is needed to implement PROAST before it can be used. Further, it may be helpful if users learn some of the basic features of R.

Installation

Unfortunately, the download does not function. We are working on the problem. Please contact proast@rivm.nl for the latest version of PROAST.

R users: Open the word document “Installing R and PROAST.doc”, and follow the instructions for downloading R from the internet, and for installing Proast.

If you are going to work with PROAST for the first time, it may be helpful to just mimic the examples presented in the manual (section 4). You may also do the exercises provided in "Exercises with PROAST26.6.doc”. You may check your answers using “Answers to BMD exercises.doc”.  

For further options in PROAST, see the manual (“Proastmanual-V26.6.doc”).

Updates

If you are interested to be informed about new updates of PROAST, or other relevant information, send your email to: proast@rivm.nl