RESUMEN
Background: Spinal cord stimulation (SCS) is a treatment for chronic intractable pain powered by an implantable pulse generator that may be rechargeable or not rechargeable (NR). It is performed in 2 stages (a trialing phase followed by permanent device implantation) and necessitates 2 hospitalizations, which may increase infection risk. Objective: This analysis explores the cost impact of improvements in battery longevity and the adoption of 1-step (direct-to-implant [DTI]) SCS implantation. Methods: Since 2019, 3 leading NR-SCS devices have been launched: Device A (2019), Device B (2020), and Device C (2021). The battery longevity of the newest Device C was estimated at comparable stimulation settings for Devices A and B. A Markov model simulated individual patient pathways across 2 scenarios: Device A vs Device C and Device B vs Device C (both with the DTI approach and 2-step approach). Costs considered were the initial device implantation procedure, device replacements, and serious adverse event (SAE) management. Italian diagnosis-related group (DRG) tariffs were applied for costs, and a 15-year time horizon was used. Results: Over 15 years, using a DTI approach, the undiscounted total costs for Device A vs Device C were 26 860 and 22 633, respectively, and 25 111 and 22 399 for Device B vs Device C, respectively. Compared with Devices A and B, Device C offered savings of 4227 and 2712, respectively; similar savings were predicted with a 2-step implant approach. Discussion: The battery longevity of NR-SCS devices directly impacts long-term costs to a payer. The longer the device lasts, the lower mean total cumulative costs the patient will have, especially with regard to device replacement costs. With novel devices and specific programming settings, the lifetime cost per patient to a payer can be decreased without compromising the patient's safety and positive clinical outcome. Conclusions: Extended SCS battery longevity can translate into tangible cost savings for payers. The DTI approach for SCS supports National Healthcare System cost efficiencies and offers the additional benefits of optimizing operating room time while having only one recovery period for the patient.
RESUMEN
There is considerable interest in biomedical applications of quantum dot (QD) nanoparticles, in particular their use as imaging agents for diagnostic applications. In order to investigate the in vivo biodistribution and the potential toxicity of quantum dots (QDs), it is crucial to develop pharmacokinetic (PK) models as basis for prediction of QDs exposure profiles over time. Here, we investigated the in vivo biodistribution of novel indium-based QDs in mice for up to three months after intravenous administration and subsequently developed a translational population PK model to scale findings to humans. This evaluation was complemented by a comprehensive overview of the in vivo toxicology of QDs in rats. The QDs were primarily taken up by the liver and spleen and were excreted via hepatobiliary and urinary pathways. A non-linear mixed effects modelling approach was used to describe blood and organ disposition characteristics of QDs using a multi-compartment PK model. The observed blood and tissue exposure to QDs was characterised with an acceptable level of accuracy at short and long-term. Of note is the fast distribution of QDs from blood into liver and spleen in the first 24 h post-injection (half-life of 28 min) followed by a long elimination profile (half-life range: 47-90 days). This is the first study to assess the PK properties of QDs using a population pharmacokinetic approach to analyse in vivo preclinical data. No organ damage was observed following systemic administration of QDs at doses as high as 48 mg/kg at 24 h, 1 week and 5 weeks post-injection. In conjunction with the data arising from the toxicology experiments, PK parameter estimates provide insight into the potential PK properties of QDs in humans, which ultimately allow prediction of their disposition and enable optimisation of the design of first-in-human QDs studies.