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 in human risk assessment, or an ECx in ecotoxicological risk assessment.
Currently, PROAST is based on multiple choice questions that the reader should answer which makes it easy to use. 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 either S-plus or R.

Installation

Download the zip file PROAST20.2 (1468Kb) to your computer. Unzip this file, and you will see a number of files. If you are not a user of S-plus (commercial software), you can use PROAST within the package R (freeware).

S-plus users: If you are an S-plus user, go directly to the PROAST manual (section 2.2) for instructions.

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. Note that the file “PROAST20.2.zip” must not be unzipped, otherwise installation will fail.

If you are going to work with PROAST for the first time, it may be helpful to do some of the exercises provided in “Exercises with BMD approach.doc”. You may check your answers using “Answers to BMD exercises.doc”. The data needed in these exercises are given in the files with extension “.txt”. For further options in PROAST, see the manual (“Proastmanual.XX.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