Abstract: Vaccine compositions that may be administered to a subject via the buccal and/or sublingual mucosa are provided. Methods for administration and preparation of such vaccine compositions are also provided.

Abstract: Vaccine compositions that may be administered to a subject via the buccal and/or sublingual mucosa are provided. Methods for administration and preparation of such vaccine compositions are also provided.

Abstract: Vaccine compositions that may be administered to a subject via the buccal and/or sublingual mucosa are provided. Methods for administration and preparation of such vaccine compositions are also provided.

Abstract: The present disclosure generally relates to a method for providing an immune suppressive therapy, in particular by inhibiting LMBR1L (limb region 1 like) in a subject in need thereof. Also, provided herein are compositions and kits that can be used in such methods.

Abstract: Vaccine compositions that may be administered to a subject via the buccal and/or sublingual mucosa are provided. Methods for administration and preparation of such vaccine compositions are also provided.

Abstract: Vaccine compositions that may be administered to a subject via the buccal and/or sublingual mucosa are provided. Methods for administration and preparation of such vaccine compositions are also provided.

Abstract: Vaccine compositions that may be administered to a subject via the buccal and/or sublingual mucosa are provided. Methods for administration and preparation of such vaccine compositions are also provided.

Abstract: Vaccine compositions that may be administered to a subject via the buccal and/or sublingual mucosa are provided. Methods for administration and preparation of such vaccine compositions are also provided.

Abstract: The present invention relates to the system, method and program for the pharmacokinetic parameter prediction of peptide sequence by the mathematical model. The present invention is comprising the steps of acquiring a variety of peptide sequence having specific features by the experimental technique; acquiring, on the basis of the sequence, a variety of peptide sequences lacking the specific features; storing the acquired peptide sequences as each set respectively, followed by randomly extracting peptide sequences in the constant ratio to divide into a training set and a test set of mathematical model; allowing individual peptide sequence descriptor values and an activity value; training the set of training peptide by mathematical model; predicting pharmacokinetic parameter of the set of test peptide by the trained mathematical model; and validating the trained mathematical model.