Use of the Same Model or Modeling Strategy Across Multiple Submissions: Focus on Complex Drug Products.

Evidence shows that there is an increasing use of modeling and simulation to support product development and approval for complex generic drug products in the USA, which includes the use of mechanistic modeling and model-integrated evidence (MIE). The potential for model reuse was the subject of a workshop session summarized in this review, where the session included presentations and a panel discussion from members of the U.S. Food and Drug Administration (FDA), academia, and the generic drug product industry. Concepts such as platform performance assessment and MIE standardization were introduced to provide potential frameworks for model reuse related to mechanistic models and MIE, respectively. The capability of models to capture formulation and product differences was explored, and challenges with model validation were addressed for drug product classes including topical, orally inhaled, ophthalmic, and long-acting injectable drug products. An emphasis was placed on the need for communication between FDA and the generic drug industry to continue to foster maturation of modeling and simulation that may support complex generic drug product development and approval, via meetings and published guidance from FDA. The workshop session provided a snapshot of the current state of modeling and simulation for complex generic drug products and offered opportunities to explore the use of such models across multiple drug products.

Synthetic RNA modules for fine-tuning gene expression levels in yeast by modulating RNase III activity.

The design of synthetic gene networks requires an extensive genetic toolbox to control the activities and levels of protein components to achieve desired cellular functions. Recently, a novel class of RNA-based control modules, which act through post-transcriptional processing of transcripts by directed RNase III (Rnt1p) cleavage, were shown to provide predictable control over gene expression and unique properties for manipulating biological networks. Here, we increase the regulatory range of the Rnt1p control elements, by modifying a critical region for enzyme binding to its hairpin substrates, the binding stability box (BSB). We used a high throughput, cell-based selection strategy to screen a BSB library for sequences that exhibit low fluorescence and thus high Rnt1p processing efficiencies. Sixteen unique BSBs were identified that cover a range of protein expression levels, due to the ability of the sequences to affect the hairpin cleavage rate and to form active cleavable complexes with Rnt1p. We further demonstrated that the activity of synthetic Rnt1p hairpins can be rationally programmed by combining the synthetic BSBs with a set of sequences located within a different region of the hairpin that directly modulate cleavage rates, providing a modular assembly strategy for this class of RNA-based control elements.

Engineering ligand-responsive RNA controllers in yeast through the assembly of RNase III tuning modules.

The programming of cellular networks to achieve new biological functions depends on the development of genetic tools that link the presence of a molecular signal to gene-regulatory activity. Recently, a set of engineered RNA controllers was described that enabled predictable tuning of gene expression in the yeast Saccharomyces cerevisiae through directed cleavage of transcripts by an RNase III enzyme, Rnt1p. Here, we describe a strategy for building a new class of RNA sensing-actuation devices based on direct integration of RNA aptamers into a region of the Rnt1p hairpin that modulates Rnt1p cleavage rates. We demonstrate that ligand binding to the integrated aptamer domain is associated with a structural change sufficient to inhibit Rnt1p processing. Three tuning strategies based on the incorporation of different functional modules into the Rnt1p switch platform were demonstrated to optimize switch dynamics and ligand responsiveness. We further demonstrated that these tuning modules can be implemented combinatorially in a predictable manner to further improve the regulatory response properties of the switch. The modularity and tunability of the Rnt1p switch platform will allow for rapid optimization and tailoring of this gene control device, thus providing a useful tool for the design of complex genetic networks in yeast.

A synthetic library of RNA control modules for predictable tuning of gene expression in yeast.

Advances in synthetic biology have resulted in the development of genetic tools that support the design of complex biological systems encoding desired functions. The majority of efforts have focused on the development of regulatory tools in bacteria, whereas fewer tools exist for the tuning of expression levels in eukaryotic organisms. Here, we describe a novel class of RNA-based control modules that provide predictable tuning of expression levels in the yeast Saccharomyces cerevisiae. A library of synthetic control modules that act through posttranscriptional RNase cleavage mechanisms was generated through an in vivo screen, in which structural engineering methods were applied to enhance the insulation and modularity of the resulting components. This new class of control elements can be combined with any promoter to support titration of regulatory strategies encoded in transcriptional regulators and thus more sophisticated control schemes. We applied these synthetic controllers to the systematic titration of flux through the ergosterol biosynthesis pathway, providing insight into endogenous control strategies and highlighting the utility of this control module library for manipulating and probing biological systems.

In Silico Methods for Development of Generic Drug-Device Combination Orally Inhaled Drug Products.

The development of generic, single-entity, drug-device combination products for orally inhaled drug products is challenging in part because of the complex nature of device design characteristics and the difficulties associated with establishing bioequivalence for a locally acting drug product delivered to the site of action in the lung. This review examines in silico models that may be used to support the development of generic orally inhaled drug products and how model credibility may be assessed.

Impact of Vehicle Physicochemical Properties on Modeling-Based Predictions of Cyclosporine Ophthalmic Emulsion Bioavailability and Tear Film Breakup Time.

Several physicochemical parameters are thought to affect in vivo performance of cyclosporine ophthalmic emulsion, including globule size distribution, viscosity profile as a function of applied shear, pH, zeta potential, osmolality, and surface tension. Using a modeling approach, this study predicts cyclosporine ophthalmic emulsion drug bioavailability to the cornea and conjunctiva and tear film breakup time for human subjects as a function of the vehicle physicochemical properties viscosity, surface tension, and osmolality for products that are qualitatively (Q1) and quantitatively (Q2) the same. The change in tear film breakup time from baseline, a potential indirect measure of therapeutic benefit, was predicted to characterize the direct effect of the vehicle on efficacy. Bioavailability predictions showed that while individual predictions were sensitive to variations in corneal and conjunctival permeabilities, geometric mean ratios of the test-to-reference comparisons for formulations that are Q1 and Q2 the same showed little sensitivity. Parameter sensitivity analysis showed that bioavailability and change in tear film breakup time from baseline values were both very sensitive to viscosity, slightly sensitive to surface tension, and insensitive to osmolality. With further improvements, the modeling framework developed for this study may be useful for informing future recommendations of cyclosporine ophthalmic emulsion bioequivalence for potential generic drug products.

Application of Physiologically Based Absorption Modeling for Amphetamine Salts Drug Products in Generic Drug Evaluation.

Amphetamine (AMP) salts-based extended-release (ER) drug products are widely used for the treatment of attention deficit hyperactivity disorder. We developed physiologically based absorption models for mixed AMP salts ER capsules and dextroamphetamine sulfate ER capsules to address specific questions raised during generic drug postmarketing surveillance and bioequivalence (BE) guidance development. The models were verified against several data sets. Virtual BE simulations were conducted to assess BE in various populations other than normal healthy subjects where BE studies are generally conducted for approval. The models were also used to predict pharmacokinetics (PK) for hypothetical formulations having dissolution profiles falling within specification after the development of in vitro-in vivo relation. Finally, we demonstrated how to use the models to test sensitivity of PK metrics to the changes in formulation variables.