2017 in review: FDA approvals of new molecular entities.

An overview of drugs approved by the FDA in 2017 reflected a reversion to the mean after a low number of NME approvals in 2016. This reversal was largely driven by the largest number of biologics-based NMEs recorded to date, which offset an average number of small-molecule approvals. Oncology indications continued to dominate followed by novel treatments for infectious, immunologic and neurologic diseases. From a mechanistic standpoint, the industry has continued a trend of target diversification, reflecting advances in scientific understanding of disease processes. Finally, 2017 continued a period of relatively few mergers and acquisitions, which broke a more-than-a-decade-long decline in the number of organizations contributing to research and development.

Toward quantitative quasistatic elastography with a gravity-induced deformation source for image-guided breast surgery.

Biomechanical breast models have been employed for applications in image registration and diagnostic analysis, breast augmentation simulation, and for surgical and biopsy guidance. Accurate applications of stress-strain relationships of tissue within the breast can improve the accuracy of biomechanical models that attempt to simulate breast deformations. Reported stiffness values for adipose, glandular, and cancerous tissue types vary greatly. Variations in reported stiffness properties have been attributed to differences in testing methodologies and assumptions, measurement errors, and natural interpatient differences in tissue elasticity. Therefore, the ability to determine patient-specific in vivo breast tissue properties would be advantageous for these procedural applications. While some in vivo elastography methods are not quantitative and others do not measure material properties under deformation conditions that are appropriate to the application of concern, in this study, we developed an elasticity estimation method that is performed using deformations representative of supine therapeutic procedures. More specifically, reconstruction of mechanical properties appropriate for the standard-of-care supine lumpectomy was performed by iteratively fitting two anatomical images before and after deformations taking place in the supine breast configuration. The method proposed is workflow-friendly, quantitative, and uses a noncontact, gravity-induced deformation source.

2016 in review: FDA approvals of new molecular entities.

An overview of drugs approved by FDA in 2016 reveals dramatic disruptions in long-term trends. The number of new molecular entities (NMEs) dropped, reflecting the lowest rate of small-molecule approvals observed in almost five decades. In addition, the pace of industry consolidation slowed substantially. The impact of mergers and acquisitions decreased the total number of organizations with past approval experience and continued research and development (R&D) activities to 102, divided evenly between more established pharmaceutical and newer biotechnology companies. Despite these substantial differences, the industry continued to pursue regulatory incentives, as evidenced by a continued increase in the fraction of NMEs approved using an orphan or priority designation, and almost all oncology drugs approved in 2016 utilized these mechanisms.

Breast tissue stiffness estimation for surgical guidance using gravity-induced excitation.

Tissue stiffness interrogation is fundamental in breast cancer diagnosis and treatment. Furthermore, biomechanical models for predicting breast deformations have been created for several breast cancer applications. Within these applications, constitutive mechanical properties must be defined and the accuracy of this estimation directly impacts the overall performance of the model. In this study, we present an image-derived computational framework to obtain quantitative, patient specific stiffness properties for application in image-guided breast cancer surgery and interventions. The method uses two MR acquisitions of the breast in different supine gravity-loaded configurations to fit mechanical properties to a biomechanical breast model. A reproducibility assessment of the method was performed in a test-retest study using healthy volunteers and was further characterized in simulation. In five human data sets, the within subject coefficient of variation ranged from 10.7% to 27% and the intraclass correlation coefficient ranged from 0.91-0.944 for assessment of fibroglandular and adipose tissue stiffness. In simulation, fibroglandular content and deformation magnitude were shown to have significant effects on the shape and convexity of the objective function defined by image similarity. These observations provide an important step forward in characterizing the use of nonrigid image registration methodologies in conjunction with biomechanical models to estimate tissue stiffness. In addition, the results suggest that stiffness estimation methods using gravity-induced excitation can reliably and feasibly be implemented in breast cancer surgery/intervention workflows.

Android application for determining surgical variables in brain-tumor resection procedures.

The fidelity of image-guided neurosurgical procedures is often compromised due to the mechanical deformations that occur during surgery. In recent work, a framework was developed to predict the extent of this brain shift in brain-tumor resection procedures. The approach uses preoperatively determined surgical variables to predict brain shift and then subsequently corrects the patient's preoperative image volume to more closely match the intraoperative state of the patient's brain. However, a clinical workflow difficulty with the execution of this framework is the preoperative acquisition of surgical variables. To simplify and expedite this process, an Android, Java-based application was developed for tablets to provide neurosurgeons with the ability to manipulate three-dimensional models of the patient's neuroanatomy and determine an expected head orientation, craniotomy size and location, and trajectory to be taken into the tumor. These variables can then be exported for use as inputs to the biomechanical model associated with the correction framework. A multisurgeon, multicase mock trial was conducted to compare the accuracy of the virtual plan to that of a mock physical surgery. It was concluded that the Android application was an accurate, efficient, and timely method for planning surgical variables.